Search results “Analysis data using spss”

Use simple data analysis techniques in SPSS to analyze survey questions.

Views: 875134
Claus Ebster

Views: 87615
Ross Avilla

Updated video 2018: SPSS for Beginners - Introduction https://youtu.be/_zFBUfZEBWQ
This video provides an introduction to SPSS/PASW. It shows how to navigate between Data View and Variable View, and shows how to modify properties of variables.

Views: 1619685
Research By Design

How to enter and analyze questionnaire (survey) data in SPSS is illustrated in this video. Lots more Questionnaire/Survey & SPSS Videos here: https://www.udemy.com/survey-data/?couponCode=SurveyLikertVideosYT
Check out our next text, 'SPSS Cheat Sheet,' here: http://goo.gl/b8sRHa. Prime and ‘Unlimited’ members, get our text for free. (Only 4.99 otherwise, but likely to increase soon.)
Survey data
Survey data entry
Questionnaire data entry
Channel Description: https://www.youtube.com/user/statisticsinstructor
For step by step help with statistics, with a focus on SPSS. Both descriptive and inferential statistics covered. For descriptive statistics, topics covered include: mean, median, and mode in spss, standard deviation and variance in spss, bar charts in spss, histograms in spss, bivariate scatterplots in spss, stem and leaf plots in spss, frequency distribution tables in spss, creating labels in spss, sorting variables in spss, inserting variables in spss, inserting rows in spss, and modifying default options in spss. For inferential statistics, topics covered include: t tests in spss, anova in spss, correlation in spss, regression in spss, chi square in spss, and MANOVA in spss. New videos regularly posted. Subscribe today!
YouTube Channel: https://www.youtube.com/user/statisticsinstructor
Video Transcript:
In this video we'll take a look at how to enter questionnaire or survey data into SPSS and this is something that a lot of people have questions with so it's important to make sure when you're working with SPSS in particular when you're entering data from a survey that you know how to do. Let's go ahead and take a few moments to look at that. And here you see on the right-hand side of your screen I have a questionnaire, a very short sample questionnaire that I want to enter into SPSS so we're going to create a data file and in this questionnaire here I've made a few modifications. I've underlined some variable names here and I'll talk about that more in a minute and I also put numbers in parentheses to the right of these different names and I'll also explain that as well. Now normally when someone sees this survey we wouldn't have gender underlined for example nor would we have these numbers to the right of male and female. So that's just for us, to help better understand how to enter these data. So let's go ahead and get started here. In SPSS the first thing we need to do is every time we have a possible answer such as male or female we need to create a variable in SPSS that will hold those different answers. So our first variable needs to be gender and that's why that's underlined there just to assist us as we're doing this. So we want to make sure we're in the Variable View tab and then in the first row here under Name we want to type gender and then press ENTER and that creates the variable gender. Now notice here I have two options: male and female. So when people respond or circle or check here that they're male, I need to enter into SPSS some number to indicate that. So we always want to enter numbers whenever possible into SPSS because SPSS for the vast majority of analyses performs statistical analyses on numbers not on words. So I wouldn't want and enter male, female, and so forth. I want to enter one's, two's and so on. So notice here I just arbitrarily decided males get a 1 and females get a 2. It could have been the other way around but since male was the first name listed I went and gave that 1 and then for females I gave a 2. So what we want to do in our data file here is go head and go to Values, this column, click on the None cell, notice these three dots appear they're called an ellipsis, click on that and then our first value notice here 1 is male so Value of 1 and then type Label Male and then click Add. And then our second value of 2 is for females so go ahead and enter 2 for Value and then Female, click Add and then we're done with that you want to see both of them down here and that looks good so click OK. Now those labels are in here and I'll show you how that works when we enter some numbers in a minute. OK next we have ethnicity so I'm going to call this variable ethnicity. So go ahead and type that in press ENTER and then we're going to the same thing we're going to create value labels here so 1 is African-American, 2 is Asian-American, and so on. And I'll just do that very quickly so going to Values column, click on the ellipsis. For 1 we have African American, for 2 Asian American, 3 is Caucasian, and just so you can see that here 3 is Caucasian, 4 is Hispanic, and other is 5, so let's go ahead and finish that. Four is Hispanic, 5 is other, so let's go to do that 5 is other. OK and that's it for that variable. Now we do have it says please state I'll talk about that next that's important when they can enter text we have to handle that differently.

Views: 677407
Quantitative Specialists

How to analyze a research questionnaire data that has been collected using SPSS. The proper techniques that are based on your research objectives and hypothesis are used. The analysis of the data is done by focusing on reliability of the questionnaire. Descriptive analysis, frequencies, correlation, factor analysis and regression analysis.

Views: 48694
Knowledge Abundance

VIDEO SECTIONS:
0:30 – Preparing a Data Set
10:51 – Transforming Data
17:49 – Descriptive Statistics
29:25 – SPSS Syntax Editor

Views: 541279
Meredith Rocchi

How to conduct an analysis of frequencies and descriptive statistics using SPSS/PASW.

Views: 313925
bernstmj

This video demonstrates a few ways to analyze pretest/posttest data using SPSS.

Views: 118762
Dr. Todd Grande

http://thedoctoraljourney.com/ This tutorial demonstrates how to conduct a One Way ANOVA in SPSS.
For more statistics, research and SPSS tools, visit http://thedoctoraljourney.com/.

Views: 490891
The Doctoral Journey

How to define variables and enter data into SPSS (v20)
ASK SPSS Tutorial Series

Views: 528528
BrunelASK

Multiple Response Analysis using SPSS Statistics

Views: 55833
My Easy Statistics

Views: 1920
Ross Avilla

Correspondence Analysis allows us to examine the relationship between two nominal variables graphically in a multidimensional Space.

Views: 18429
My Easy Statistics

How to Use SPSS
In this third video about SPSS for Beginners, Dr. Daniel shows you three ways to approach descriptive statistics in SPSS. If you want quick and basic descriptives, use the Descriptives command to get the most commonly used statistics. The Frequencies command gives you a wide range of possibilities with the most flexibility to choose exactly what output that you want. When you want maximum output with lots of graphs – or if you want to split the descriptive statistics by a categorical variable (like gender), then use the Explore command.
Link to a Google Drive folder with all of the files that I use in the videos including the Bear Handout and StatsClass.sav. As I add new files, they will appear here, as well.
https://drive.google.com/drive/folders/1n9aCsq5j4dQ6m_sv62ohDI69aol3rW6Q?usp=sharing

Views: 158644
Research By Design

Find the mean and standard deviation in SPSS separately for groups; for example, get a separate mean for males and females (using the compare means procedure in spss).
Check out our next text, 'SPSS Cheat Sheet,' here: http://goo.gl/b8sRHa. Prime and 'Unlimited' members, get our text for free! (Only $4.99 otherwise, but will likely increase soon.)
Obtain the mean and standard deviation separately for different groups of a variable in SPSS.
Video Transcript: In this tutorial we're going to take a look at how to obtain means for different groups of a variable on some other variable of interest. Let me show you what I mean here. So, for example, in this data set, we have two variables, play golf and satisfaction. Now play golf is coded, if I click on my Value Labels button here, I've already coded it, and you can see that we have either yes (coded 1), those who do play golf, or no (coded 2), those who do not play golf. And I want a mean for just the yes group, the 1s, and a mean for just the 2, the No's. So now we know what we want, we want the means broken down separately by the different groups. To do that we need to go to Analyze, Compare Means, Means. OK so select that and then here in our Dependent List, this is where the satisfaction variable would go, so move that over. And the Independent List will always be the categorical variable, in this case the variable, play golf. It's categorical and it happens to be dichotomous because there are only two options, a 1 or a 2, or a Yes or No. OK so play golf will go to the Independent List and then go to Options, so we can see what options are selected. I see a mean and I see a standard deviation by default and number of cases as well. We can keep number of cases, that could be helpful, but let's drag that up to the top here and have that present first in our output. OK so everything looks good here. Let's click Continue and then click OK. Now our output opens we're going to scroll down here, actually I'm going to delete a little bit of this. I'll delete this by selecting it, pressing the Delete key. I'm going to delete this here, so we can see these two tables at the same time. Here's the output of my Means procedure, the procedure we just ran. I'm just going to briefly mention this Case Processing Summary table, just to say it shows that all 7 observations were included, and none were excluded, so everything was analyzed, that's all that means. Zeroing in on this table, the Report table, this is what we want to see. Notice here I have the play golf variable and I have analyses for the Yes group the 5 people who were in the Yes group, and the No group, the two people in that group. And notice now I have means broken down separately for these two groups, which is exactly what I wanted. So the yes group, those who play golf, had an average satisfaction score of 8.20, whereas those who did not play golf had an average satisfaction score of 7.00. So you should be able to see, at least in the sample here, that those who played golf did have a higher average satisfaction score, or higher mean satisfaction score, than those who did not play golf. OK and we see the standard deviations here as well. Just as a side note this standard deviation is 0 because our two people who were in the No group both had a score of 7. If they both have a score 7, there's no variability at all in the data set for this group. So that's why we have a standard deviation of 0. One last note here. Notice the Total. See where it says 7 here, and then we have a mean of 7.86 standard deviation .90? If we go back up here to our original analysis, the analysis using Descriptive Statistics and then using the Descriptives option, notice we have the same thing: 7.86 for the mean .90 for the standard deviation. So what the Means procedure does down Here it breaks it down by the different groups, and it also gives you the overall analysis down here, which is what we got the first time by Descriptive Statistics. But anytime you want to get a mean, a descriptive analysis, but of means separately for different groups, you want to go to Analyze, Compare Means and then the Means procedure.
Lifetime access to SPSS videos: http://tinyurl.com/kuejrzz
YouTube Channel: https://www.youtube.com/user/statisticsinstructor
Subscribe today!
Channel Description: For step by step help with statistics, with a focus on statistics and SPSS. Both descriptive and inferential statistics covered.
Lifetime access to SPSS videos: http://tinyurl.com/m2532td

Views: 188020
Quantitative Specialists

In this series of Data Management using SPSS software, I have discussed Inserting a new case, Inserting a new variable into the database.
I have discussed Identification of duplication cases in the data base.
This video is very useful for beginners to learn the analysis in a step by step process.

Views: 693
My Easy Statistics

Basic introduction to correlation - how to interpret correlation coefficient, and how to chose the right type of correlation measure for your situation.
0:00 Introduction to bivariate correlation
2:20 Why does SPSS provide more than one measure for correlation?
3:26 Example 1: Pearson correlation
7:54 Example 2: Spearman (rhp), Kendall's tau-b
15:26 Example 3: correlation matrix
I could make this video real quick and just show you Pearson's correlation coefficient, which is commonly taught in a introductory stats course. However, the Pearson's correlation IS NOT always applicable as it depends on whether your data satisfies certain conditions. So to do correlation analysis, it's better I bring together all the types of measures of correlation given in SPSS in one presentation.
Watch correlation and regression: https://youtu.be/tDxeR6JT6nM
-------------------------
Correlation of 2 rodinal variables, non monotonic
This question has been asked a few times, so I will make a video on it. But to answer your question, monotonic means in one direction. I suggest you plot the 2 variables and you'll see whether or not there is a monotonic relationship there. If there is a little non-monotonic relationship then Spearman is still fine. Remember we are measuring the TENDENCY for the 2 variables to move up-up/down-down/up-down together. If you have strong non-monotonic shape in the plot ie. a curve then you could abandon correlation and do a chi-square test of association - this is the "correlation" for qualitative variables. And since your 2 variables are ordinal, they are qualitative.
Good luck

Views: 531001
Phil Chan

Links of Data set and case study used in the above video.
1. https://drive.google.com/open?id=1cFxxzm6mT1Ong4sO-qMrXHiGx_vfncb5
2. https://drive.google.com/open?id=1qGFUSLbp_T7Ei8GPxcDFLaLwQcsO0gpl

Views: 6860
Dr. Shailesh Kaushal

This video is part of the University of Southampton, Southampton Education School, Digital Media Resources
http://www.southampton.ac.uk/education
http://www.southampton.ac.uk/~sesvideo/

Views: 206581
Southampton Education School

This video demonstrates how to analysis pretest and posttest data using SPSS when there is both a between-subjects factor and a within-subjects factor. Two methods for analyzing these data will be reviewed: Analysis of Covariance (ANCOVA) and Repeated Measures Analysis of Variance (RM ANOVA).

Views: 23529
Dr. Todd Grande

Exploratory data analysis is an approach to analyzing data sets to summarize main characteristics of the data.
Exploratory data Analysis can help to determine whether the statistical technique that we are considering for data analysis are appropriate.

Views: 1983
My Easy Statistics

This video describes how to perform a factor analysis using SPSS and interpret the results.

Views: 271142
Dr. Todd Grande

0:08 Multiple choice item vs. Likert scale item
1:33 Multiple choice questions with one correct answer
3:27 Multiple choice questions with multiple correct answers
6:03 "Multiple response set" in SPSS
7:52 How to pronounce "Likert"?
This video discusses how to best enter and code multiple choice type data in SPSS as well as how to analyze such data using descriptive stats and multiple response sets.
Please LIKE this video if you enjoyed it.
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The views expressed in this video are my own and do not necessarily reflect the organizations with which I am affiliated.
#SPSS #Statistics #DataEntry #RanywayzRandom

Views: 73001
Ranywayz Random

This video provides an overview of Principal components analysis in SPSS as a data reduction technique (keep in mind the assumption is you are working with measured variables that are reasonably treated as continuous). I review basic options in SPSS, as well as discuss strategies for identifying the number of components to retain (including parallel analysis) and naming those factors. I discuss Varimax rotation and Promax rotation, as well as the generation of component scores. Finally, I illustrate how you can use component scores in subsequent analyses such as regression. This is a fairly long video, but it was aimed at being comprehensive! You can perform the same steps I illustrate by downloading the data here ( https://drive.google.com/open?id=1Ds7LXr-_NUP3FYCxcd0kxv9WHowUwGqc ) and following along.
You can go to the site referenced to carry out the parallel analysis here: https://analytics.gonzaga.edu/parallelengine/
The IBM website referencing the KMO measure of sampling adequacy is located here: http://www-01.ibm.com/support/docview.wss?uid=swg21479963
For more instructional videos and other materials on various statistics topics, be sure to my webpages at the links below:
Introductory statistics:
https://sites.google.com/view/statisticsfortherealworldagent/home
Multivariate statistics:
https://sites.google.com/view/statistics-for-the-real-world/home

Views: 10931
Mike Crowson

If data need to be approximately normally distributed, this tutorial shows how to use SPSS to verify this. On a side note: my new project: http://howtowritecitations.com.
Statistical analyses often have dependent variables and independent variables and many parametric statistical methods require that the dependent variable is approximately normally distributed for each category of the independent variable.
Let us assume that we have a dependent variable, exam scores, and an independent variable, gender.
In short, we must investigate the following numerical and visual outputs (and the tutorial shows how to do just that):
-The Skewness & kurtosis z-values, which should be somewhere in the span -1.96 to +1.96;
-The Shapiro-Wilk p-value, which should be above 0.05;
-The Histograms, Normal Q-Q plots and Box plots, which should visually indicate that our data are approximately normally distributed.
Remember that your data do not have to be perfectly normally distributed. The main thing is that they are approximately normally distributed, and that you check each category of the independent variable. (In our example, both male and female data.)
Step 1. In the menu of SPSS, click on Analyze, select Descriptive Statistics and Explore.
Step 2. Set exam scores as the dependent variable, and gender as the independent variable.
Step 3. Click on Plots, select "Histogram" (you do not need "Stem-and-leaf") and select "Normality plots with tests" and click on Continue, then OK.
Step 4. Start with skewness and kurtosis. The skewness and kurtosis measures should be as close to zero as possible, in SPSS. In reality, however, data are often skewed and kurtotic. A small departure from zero is therefore no problem, as long as the measures are not too large compare to their standard errors. As a consequence, you must divide the measure by its standard error, and you need to do this by hand, using a calculator. This will give you the z-value, which, as I said, should be somewhere within -1.96 to +1.96. Let us start with the males in our example. To calculate the skewness z-value, divide the skewness measure by its standard error. All z-values in the tutorial video are within ±1.96. We can conclude that the exam score data are a little skewed and kurtotic, for both males and females, but they do not differ significantly from normality.
Step 5. Check the Shapiro-Wilk test statistic. The null hypothesis for this test of normality is that the data are normally distributed. The null hypothesis is rejected if the p-value is below 0.05. In SPSS output, the p-value is labeled "Sig". In our example, the p-values for males and females are above 0.05, so we keep the null hypothesis. The Shapiro-Wilk test thus indicates that our example data are approximately normally distributed.
Step 6. Next, let us look at the graphical figures, for both male and female data. Inspect the histograms visually. They should have the approximate shape of a normal curve. Then, look at the normal Q-Q plot. The dots should be approximately distributed along the line. This indicates that the data are approximately normally distributed. Skip the Detrended Q-Q plots. You do not need them. Finally, look at the box plots. They should be approximately symmetrical.
The video contains references to books and articles.
About writing out the results: I would put it under the sub-heading "Sample characteristics", and the video contains examples of how I would write.
In this tutorial, I show you how to check if a dependent variable is approximately normally distributed for each category of an independent variable. I am assuming that you, eventually, want to use a certain parametric statistical methods to explore and investigate your data. If it turns out that your dependent variable is not approximately normally distributed for each category of the independent variable, it is no problem. In such case, you will have to use non-parametric methods, because they make no assumptions about the distributions.
Good luck with your research.
Text and video (including audio) © Kent Löfgren, Sweden
Here are the references that I discuss in the video (thanks Abdul Syafiq Bahrin for typing them our for me):
Cramer, D. (1998). Fundamental statistics for social research. London: Routledge.
Cramer, D., & Howitt, D. (2004). The SAGE dictionary of statistics. London: SAGE.
Doane, D. P., & Seward, L.E. (2011). Measuring Skewness. Journal of Statistics Education, 19(2), 1-18.
Razali, N. M., & Wah, Y. B. (2011). Power comparisons of Shapiro-Wilk, Kolmogorov-Smirnov, Liliefors and Anderson-Darling test. Journal of Statistical Modeling and Analytics, 2(1), 21-33.
Shapiro, S. S., & Wilk, M. B. (1965). An Analysis of Variance Test for Normality (Complete Samples). Biometrika, 52(3/4), 591-611.

Views: 463539
Kent Löfgren

A step-by-step approach for choosing an appropriate statistcal test for data analysis.

Views: 473054
TheRMUoHP Biostatistics Resource Channel

Video provides overview of ways of obtaining and interpreting descriptive statistics for variables with different scales of measurement.

Views: 22049
Mike Crowson

In this four-part demonstration videos series, you’ll gain a good understanding of SPSS Modeler's powerful capabilities including:
• Accessing data
• Manipulating data
• Analyzing data
• Deploying the results of your analysis
In this third video, learn how you can analyze your data with SPSS Modeler.
Get your free 30-day SPSS Modeler trial today: https://ibm.co/spssmodelertrial

Views: 7849
IBM Analytics

Session 18: Descriptive Statistics: Summarising and Visualising Data
Fifth Video

Views: 61664
Anthony Kuster

This video shows how to use SPSS to conduct a Correlation and Regression Analysis. A simple null hypothesis is tested as well. The regression equation is explained despite the result of the hypothesis conclusion.
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MORE VIDEOS:
Watch Using Excel to find the Correlation Coefficient r here: https://youtu.be/y3bgaLwdm50
Watch ANOVA in SPSS here: https://youtu.be/Bx9ry1vBbTM
Watch Sampling Distribution of Sample Means here: https://youtu.be/anGsd2l5YpM
Watch Using Excel Charts to calculate Regression Equation here: https://youtu.be/qZjTtnyaV70
Watch Using Excel to calculate Regression Equation here: https://youtu.be/LDC0p9iZY8g
Watch ANOVA in Microsoft Excel (One-Way) here: https://youtu.be/WhBkgWL3_3k
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Views: 245794
Agron Kaci

Using multiple predictor variables to predict a single quantitative outcome.

Views: 259115
TheRMUoHP Biostatistics Resource Channel

A visual explanation and step by step guide on how to calculate a one way ANOVA using SPSS. Tutorial includes an explanation of the results.
Like MyBookSucks on Facebook http://www.Facebook.com/partymorestudyless
Related Videos: PlayList on Two Way Anova http://www.youtube.com/playlist?list=PLWtoq-EhUJe2TjJYfZUQtuq7a0dQCnOWp

Views: 176619
statisticsfun

Learn about Likert Scales in SPSS and how to copy labels from one variable to another in this video. Entering codes for Likert Scales into SPSS is also covered.
Check out our next text, 'SPSS Cheat Sheet,' here: http://goo.gl/b8sRHa. Prime and 'Unlimited' members, get our text for free! (Only $4.99 otherwise, but will likely increase soon.)
Lots more Likert & SPSS Videos here: https://www.udemy.com/survey-data/?couponCode=SurveyLikertVideosYT
Likert scale SPSS video.
YouTube Channel: https://www.youtube.com/user/statisticsinstructor
Channel Description: For step by step help with statistics and SPSS. Both descriptive and inferential statistics covered. Subscribe today!
Video Transcript: In this video we'll take a look at how to enter value labels for a variable which will be review since we've done that before. But then I also want to show you how to apply value labels that were entered for one variable to a number of different variables which can be really useful as it's a great time saver. Here in this data set notice that I have 10 people and I have the variables gender, item 1, 2, 3, 4, and 5. And they answered on what's known as a Likert scale. Now you very well may have heard of a Likert scale before and the first thing is you may have heard of it called LIKE-ERT scale which is very common to call it that but it's actually Likert, so it's pronounced LICK-ERT instead of LIKE-ERT and it was developed by Rensis Likert in the early to middle 1900s he developed the scale. And it's used so commonly, it's used in this 5-point option as you see here, 5 to 1, and we'll talk about that in just a moment. You'll also see it in a 7-point option, it's very commonly used that way. And less commonly so but you'll see it in other ways like 9-point scale and so forth. And it's used with many different kinds of descriptions like definitely true, somewhat true, and so forth; not just agree as you see here. So, in the most traditional use of this scale, which is what we see right here, we have a 5=strongly agree, a 4=agree, 3 is neither agree nor disagree - this is sometimes called neutral - 2 is disagree and then 1 is strongly disagree. On item 1 they would read the following statement: I can turn to others for support when needed. And then what they do is they read that item, they look at these 5 options, and if it's someone who has a lot of support in their network or friendships or what have you, they might answer 5, strongly agree, or 4, agree. And if it's someone who doesn't experience a lot of social support, they might answer a 1 for strongly disagree or a 2 for disagree and so on. So, the first person here in row 1, notice for item 1 they answered a 4, so they answered agree. Item 2 they answered a 5 for strongly agree and so on. If we look down item 1, did anyone answer strongly disagree - let's take a look at that. We're looking for a 1 here, and notice that participant number 9, they answered a 1 on item 1, so they answered strongly disagree, and so on. So what I want to do here is go ahead and enter the value labels for item 1 so we're going to enter these into SPSS that you see here. And then I want to show you how to apply those to the remaining items in a very quick way. First of all, notice that we have gender, if I click on my value labels button here as a review, gender is already coded, I already entered those. But what I don't have entered is item 1, item 2, 3, 4, and 5. And I'd like to go ahead and enter those to have them in the dataset, so if I go back and look at this file at a later time, I'll remember that a 5 corresponded to strongly agree and a 1 corresponded to strongly disagree, so in other words I'll know which direction this scale is scored, and what I mean by that is higher scores indicate greater social support because people strongly agreed with a given item. Whereas lower scores indicated less social support. Since we're looking at entering value labels, let's begin with item 1. So I could either double-click on item 1 or I could go to the variable view tab. Let's go ahead and double-click on item 1 right at the column heading here that's "name". So I double-click on that and notice it takes me to the variable view window. So that's a quick way to get there if you want to access the variable view window. And then we'll go to the "values" column here, click on the "None" cell and then notice the 3 dots appear. So I click on that and then here let's start with
Lifetime access to SPSS videos: http://tinyurl.com/m2532td
Video on adding Likert items together to create a total score: http://youtu.be/7jxpSLZCBsw
Likert Scales
Likert
Strongly Agree to Strongly Disagree
Likert in SPSS

Views: 197617
Quantitative Specialists

Updated video: SPSS for Beginners – Correlation https://youtu.be/6EH5DSaCF_8
This video demonstrates how to calculate correlations in SPSS and how to interpret correlation matrices.

Views: 467460
Research By Design

This 2-day workshop organized by IRP through a live webinar. Please share our channel with your friends and colleagues. You may visit our website:
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Views: 386
IRP Analytics

Discriminant analysis using SPSS: Discriminant analysis is a technique that is used by the researcher to analyze the research data when the dependent variable is categorical and the independent variable is an interval in nature.
This video explains conducting Discriminant Analysis using SPSS in a simple and easy way.
You can observe other Multivariate data analysis methods in my youtube channel.
Please, press the like button and share the video.

Views: 16072
My Easy Statistics

The content applies to qualitative data analysis in general. Do not forget to share this Youtube link with your friends.
The steps are also described in writing below (Click Show more):
STEP 1, reading the transcripts
1.1. Browse through all transcripts, as a whole.
1.2. Make notes about your impressions.
1.3. Read the transcripts again, one by one.
1.4. Read very carefully, line by line.
STEP 2, labeling relevant pieces
2.1. Label relevant words, phrases, sentences, or sections.
2.2. Labels can be about actions, activities, concepts, differences, opinions, processes, or whatever you think is relevant.
2.3. You might decide that something is relevant to code because:
*it is repeated in several places;
*the interviewee explicitly states that it is important;
*you have read about something similar in reports, e.g. scientific articles;
*it reminds you of a theory or a concept;
*or for some other reason that you think is relevant.
You can use preconceived theories and concepts, be open-minded, aim for a description of things that are superficial, or aim for a conceptualization of underlying patterns. It is all up to you.
It is your study and your choice of methodology. You are the interpreter and these phenomena are highlighted because you consider them important. Just make sure that you tell your reader about your methodology, under the heading Method. Be unbiased, stay close to the data, i.e. the transcripts, and do not hesitate to code plenty of phenomena. You can have lots of codes, even hundreds.
STEP 3, decide which codes are the most important, and create categories by bringing several codes together
3.1. Go through all the codes created in the previous step. Read them, with a pen in your hand.
3.2. You can create new codes by combining two or more codes.
3.3. You do not have to use all the codes that you created in the previous step.
3.4. In fact, many of these initial codes can now be dropped.
3.5. Keep the codes that you think are important and group them together in the way you want.
3.6. Create categories. (You can call them themes if you want.)
3.7. The categories do not have to be of the same type. They can be about objects, processes, differences, or whatever.
3.8. Be unbiased, creative and open-minded.
3.9. Your work now, compared to the previous steps, is on a more general, abstract level. You are conceptualizing your data.
STEP 4, label categories and decide which are the most relevant and how they are connected to each other
4.1. Label the categories. Here are some examples:
Adaptation (Category)
Updating rulebook (sub-category)
Changing schedule (sub-category)
New routines (sub-category)
Seeking information (Category)
Talking to colleagues (sub-category)
Reading journals (sub-category)
Attending meetings (sub-category)
Problem solving (Category)
Locate and fix problems fast (sub-category)
Quick alarm systems (sub-category)
4.2. Describe the connections between them.
4.3. The categories and the connections are the main result of your study. It is new knowledge about the world, from the perspective of the participants in your study.
STEP 5, some options
5.1. Decide if there is a hierarchy among the categories.
5.2. Decide if one category is more important than the other.
5.3. Draw a figure to summarize your results.
STEP 6, write up your results
6.1. Under the heading Results, describe the categories and how they are connected. Use a neutral voice, and do not interpret your results.
6.2. Under the heading Discussion, write out your interpretations and discuss your results. Interpret the results in light of, for example:
*results from similar, previous studies published in relevant scientific journals;
*theories or concepts from your field;
*other relevant aspects.
STEP 7 Ending remark
Nb: it is also OK not to divide the data into segments. Narrative analysis of interview transcripts, for example, does not rely on the fragmentation of the interview data. (Narrative analysis is not discussed in this tutorial.)
Further, I have assumed that your task is to make sense of a lot of unstructured data, i.e. that you have qualitative data in the form of interview transcripts. However, remember that most of the things I have said in this tutorial are basic, and also apply to qualitative analysis in general. You can use the steps described in this tutorial to analyze:
*notes from participatory observations;
*documents;
*web pages;
*or other types of qualitative data.
STEP 8 Suggested reading
Alan Bryman's book: 'Social Research Methods' published by Oxford University Press.
Steinar Kvale's and Svend Brinkmann's book 'InterViews: Learning the Craft of Qualitative Research Interviewing' published by SAGE.
Text and video (including audio) © Kent Löfgren, Sweden

Views: 795506
Kent Löfgren

This is the first of two videos that run through the process of performing and interpreting ordinal regression using SPSS.

Views: 98257
StatRegMethEdu

Repeated measures analyse an introduction to the Mixed models (random effects) option in SPSS. Demonstrates different Covariance matrix types & how to use the Likelihood ratio test to evaluate different models.
Robin Beaumont
Full notes, MCQ's etc at:
www.robin-beaumont.co.uk/virtualclassroom/stats/course2.html

Views: 183762
Robin Beaumont

How to Use SPSS
Having learned how to create a variable, you are ready to begin entering data. You will use these same data for the remaining videos. Dr. Daniel shows you how to do some basic data cleaning and data exploration with the Frequencies command in SPSS. The frequencies output will be useful later for creating a frequency table.
Link to a Google Drive folder with all of the files that I use in the videos including the Bear Handout and StatsClass.sav. As I add new files, they will appear here, as well.
https://drive.google.com/drive/folders/1n9aCsq5j4dQ6m_sv62ohDI69aol3rW6Q?usp=sharing

Views: 142869
Research By Design

In this video, I present to you a tutorial (in ARABIC) on the basics of SPSS. We will perform basic data entry, data analysis and create tables and graphs.
SPSS is capable of handling large amounts of data and can perform all of the analyses covered in the upcoming videos. I hope you will find the content helpful.
All the best and GOOD LUCK!

Views: 1431
Abdelrahman Zamzam

This video provides a demonstration of the use of Cox Proportional Hazards (regression) model based on example data provided in Luke & Homan (1998).
A copy of the data can be downloaded here: https://drive.google.com/open?id=1y6TLqz8fcWqAz1nzDdR9WkkDQ1DBI7Dg
Article cite:
Luke, D.A., & Homan, S.M. (1998). Time and change: Using survival analysis in clinical assessment and treatment evaluation. Psychological Assessment, 10, 360-378.
For more instructional videos and other materials on various statistics topics, be sure to my webpages at the links below:
Introductory statistics:
https://sites.google.com/view/statisticsfortherealworldagent/home
Multivariate statistics:
https://sites.google.com/view/statistics-for-the-real-world/home

Views: 12379
Mike Crowson

How to Use SPSS
This is the first in a series of eight videos that will introduce you to using SPSS for introductory statistics. This series is designed for people with little or no experience with SPSS. You will learn about the SPSS work space, how to navigate between Data View and Variable View, how to create variables, and how to modify properties of variables.
Link to a Google Drive folder with all of the files that I use in the videos including the Bear Handout and StatsClass.sav. As I add new files, they will appear here, as well.
https://drive.google.com/drive/folders/1n9aCsq5j4dQ6m_sv62ohDI69aol3rW6Q?usp=sharing

Views: 268321
Research By Design

This video describes the procedure of tabulating and analyzing the likert scale survey data using Microsoft Excel. This video also explains how to prepare graph from the tabulated data.
Photo courtesy: http://littlevisuals.co/

Views: 140913
Edifo

This video describes how to use ANCOVA to analyze pretest and posttest data, including how to test for the assumptions of ANCOVA.

Views: 56299
Dr. Todd Grande

This video provides a demonstration of options available through SPSS for carrying out binary logistic regression. It illustrates two available routes (through the regression module and the generalized linear models module). If you wish to download the data and follow along, you can do so by going here: https://drive.google.com/open?id=13vJ_GnjlKwCEWX7hB-CJME1Tu5jcJydQ
For more instructional videos and other materials on various statistics topics, be sure to my webpages at the links below:
Introductory statistics:
https://sites.google.com/view/statisticsfortherealworldagent/home
Multivariate statistics:
https://sites.google.com/view/statistics-for-the-real-world/home

Views: 44615
Mike Crowson

Technique for replacing missing data using the regression method. Appropriate for data that may be missing randomly or non-randomly. Also appropriate for data that will be used in inferential analysis. Determining randomness of missing data can be confirmed with Little's MCAR Test (http://youtu.be/6ybgVTabJ6s).
Resources:
FAQ- http://sites.stat.psu.edu/~jls/mifaq.html
Schafer, Joseph L. "Multiple imputation: a primer." Statistical methods in medical research 8.1 (1999): 3-15.
Sterne, Jonathan AC, et al. "Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls." BMJ: British Medical Journal 338 (2009).
McKnight, Patrick E., Katherine M. McKnight, and Aurelio Jose Figueredo. Missing data: A gentle introduction. Guilford Press, 2007.
Haukoos, Jason S., and Craig D. Newgard. "Advanced statistics: missing data in clinical research—part 1: an introduction and conceptual framework." Academic Emergency Medicine 14.7 (2007): 662-668.
Newgard, Craig D., and Jason S. Haukoos. "Advanced statistics: missing data in clinical research—part 2: multiple imputation." Academic Emergency Medicine 14.7 (2007): 669-678.

Views: 189345
TheRMUoHP Biostatistics Resource Channel

© 2019 Articles on language teaching and learning

Pool Accessary Options. Types of Pool Water Sanitation. There are a variety of pool water treatment options beyond the traditional chlorine, although it remains the most popular option. Chlorine is added to a pool to combat algae or other bacteria that can gather in the water. Chlorinated water relies on a proper pH balance to prevent an overly chemical-smelling pool. While saline pools, also known as saltwater pools, are not chlorine-free, they consist of a salt-chlorine generator that produces lower levels of chlorine. Mineral water pools are chlorine-free and use disinfecting minerals to prevent bacteria and algae. Pool Maintenance.