SPSS For Research
Focused View
Bogdan Anastasiei
14:03:09
17 View
001 Introduction.mp4
04:54
002 Course Outline.mp4
04:51
001 Guide 1 Working With SPSS Files.mp4
02:41
002 Guide 2 Defining Variables.mp4
12:08
002 Guide-2-Define-Vars.pdf
003 Guide 3 Variable Recoding.mp4
09:29
003 Guide-3-Recode.pdf
004 Guide 4 Dummy Variables.mp4
07:52
004 Guide-4-Dummy.pdf
005 Guide 5 Selecting Cases.mp4
07:11
005 Guide-5-Select.pdf
006 Guide 6 File Splitting.mp4
02:52
006 Guide-6-Split-File.pdf
007 Guide 7 Data Weighting.mp4
11:09
007 Guide-7-Weighing.pdf
001 Guide 8 Column Charts.mp4
06:41
001 Guide-8-Column.pdf
002 Guide 9 Line Charts.mp4
04:35
002 Guide-9-Line.pdf
003 Guide 10 Scatterplot Charts.mp4
04:06
003 Guide-10-Scatter.pdf
004 Guide 11 Boxplot Diagrams.mp4
04:24
004 Guide-11-Boxplot.pdf
001 Guide 12 Frequencies Procedure.mp4
05:47
001 Guide-12-Frequencies.pdf
002 Guide 13 Descriptives Procedure.mp4
01:56
002 Guide-13-Descriptives.pdf
003 Guide 14 Explore Procedure.mp4
05:09
003 Guide-14-Explore.pdf
004 Guide 15 Means Procedure.mp4
03:23
004 Guide-15-Means.pdf
005 Guide 16 Crosstabs Procedure.mp4
03:21
005 Guide-16-Crosstabs.pdf
001 Guide 17 Checking for Normality - Numerical Methods.mp4
06:34
002 Guide 17 Checking for Normality - Graphical Methods.mp4
03:33
003 Guide 17 Checking for Normality - What to Do If We Do Not Have Normality.mp4
02:08
003 Guide-17-Normality.pdf
004 Guide 18 Detecting Outliers - Graphical Methods.mp4
03:38
005 Guide 18 Detecting Outliers - Numerical Methods.mp4
03:30
006 Guide 18 Detecting Outliers - How to Handle the Outliers.mp4
03:12
006 Guide-18-Outliers.pdf
007 Guide 19 Data Transformations.mp4
08:52
007 Guide-19-Transfromations.pdf
001 Guide 20 One-Sample T Test - Introduction.mp4
04:08
002 Guide 20 One-Sample T Test - Running the Procedure.mp4
03:17
002 Guide-20-Onesample-T.pdf
003 Guide 21 Binomial Test.mp4
04:51
004 Guide 21 Binomial Test with Weighted Data.mp4
03:45
004 Guide-21-Binomial.pdf
005 Guide 22 Chi Square for Goodness-of-Fit.mp4
05:40
006 Guide 22 Chi Square for Goodness-of-Fit with Weighted Data.mp4
02:43
006 Guide-22-Chi-Goodness.pdf
001 Guide 23 Pearson Correlation - Introduction.mp4
03:56
002 Guide 23 Pearson Correlation - Assumption Checking.mp4
03:58
003 Guide 23 Pearson Correlation - Running the Procedure.mp4
03:23
003 Guide-23-Pearson.pdf
004 Guide 24 Spearman Correlation - Introduction.mp4
05:12
005 Guide 24 Spearman Correlation - Running the Procedure.mp4
02:43
005 Guide-24-Spearman.pdf
006 Guide 25 Partial Correlation - Introduction.mp4
05:33
007 Guide 25 Partial Correlation - Practical Example.mp4
03:46
007 Guide-25-Partial-Correl.pdf
008 Guide 26 Chi Square For Association.mp4
06:36
009 Guide 26 Chi Square For Association with Weighted Data.mp4
03:54
009 Guide-26-Chi-Association.pdf
010 Guide 27 Loglinear Analysis - Introduction.mp4
10:19
011 Guide 27 Loglinear Analysis - Hierarchical Loglinear Analysis.mp4
07:30
012 Guide 27 Loglinear Analysis - General Loglinear Analysis.mp4
12:27
012 Guide-27-Loglinear.pdf
001 Guide 28 Independent-Sample T Test - Introduction.mp4
04:13
002 Guide 28 Independent-Sample T Test - Assumption Testing.mp4
01:36
003 Guide 28 Independent-Sample T Test - Results Interpretation.mp4
05:09
003 Guide-28-Independent-T.pdf
004 Guide 29 Paired-Sample T Test - Introduction.mp4
03:13
005 Guide 29 Paired-Sample T Test - Assumption Testing.mp4
02:50
006 Guide 29 Paired-Sample T Test - Results Interpretation.mp4
02:48
006 Guide-29-Paired-T.pdf
007 Guide 30 One-Way ANOVA - Introduction.mp4
05:17
008 Guide 30 One-Way ANOVA - Assumption Testing.mp4
02:34
009 Guide 30 One-Way ANOVA - F Test Results.mp4
05:04
010 Guide 30 One-Way ANOVA - Multiple Comparisons.mp4
06:47
010 Guide-30-Oneway.pdf
011 Guide 31 Two-Way ANOVA - Introduction.mp4
07:15
012 Guide 31 Two-Way ANOVA - Assumption Testing.mp4
04:16
013 Guide 31 Two-Way ANOVA - Interaction Effect.mp4
08:46
014 Guide 31 Two-Way ANOVA - Simple Main Effects.mp4
13:14
014 Guide-31-Twoway.pdf
015 Guide 32 Three-Way ANOVA - Introduction.mp4
09:04
016 Guide 32 Three-Way ANOVA - Assumption Testing.mp4
03:04
017 Guide 32 Three-Way ANOVA - Third Order Interaction.mp4
04:48
018 Guide 32 Three-Way ANOVA - Simple Second Order Interaction.mp4
03:55
019 Guide 32 Three-Way ANOVA - Simple Main Effects.mp4
06:26
020 Guide 32 Three-Way ANOVA - Simple Comparisons (1).mp4
13:19
021 Guide 32 Three-Way ANOVA - Simple Comparisons (2).mp4
03:07
021 Guide-32-Threeway.pdf
022 Guide 33 Multivariate ANOVA - Introduction.mp4
04:37
023 Guide 33 Multivariate ANOVA - Assumption Checking (1).mp4
07:34
024 Guide 33 Multivariate ANOVA - Assumption Checking (2).mp4
04:39
025 Guide 33 Multivariate ANOVA - Result Interpretation.mp4
09:43
025 Guide-33-Multivariate-Anova.pdf
026 Guide 34 Analysis of Covariance (ANCOVA) - Introduction.mp4
05:08
027 Guide 34 Analysis of Covariance (ANCOVA) - Assumption Checking (1).mp4
05:16
028 Guide 34 Analysis of Covariance (ANCOVA) - Assumption Checking (2).mp4
07:08
029 Guide 34 Analysis of Covariance (ANCOVA) - Results Intepretation.mp4
03:26
029 Guide-34-Ancova.pdf
030 Guide 35 Repeated Measures ANOVA - Introduction.mp4
03:32
031 Guide 35 Repeated Measures ANOVA - Assumption Checking.mp4
01:52
032 Guide 35 Repeated Measures ANOVA - Results Interpretation.mp4
10:31
032 Guide-35-36-Repeated-Measures.pdf
033 Guide 36 Within-Within Subjects ANOVA - Introduction.mp4
03:58
034 Guide 36 Within-Within Subjects ANOVA - Assumption Checking.mp4
06:52
035 Guide 36 Within-Within Subjects ANOVA - Interaction.mp4
04:11
036 Guide 36 Within-Within Subjects ANOVA - Simple Main Effects (1).mp4
07:29
037 Guide 36 Within-Within Subjects ANOVA - Simple Main Effects (2).mp4
05:01
038 Guide 36 Within-Within Subjects ANOVA - Case of Nonsignificant Interaction.mp4
02:49
039 Guide 37 Mixed ANOVA - Introduction.mp4
03:20
040 Guide 37 Mixed ANOVA - Assumption Checking.mp4
02:45
041 Guide 37 Mixed ANOVA - Interaction.mp4
08:24
042 Guide 37 Mixed ANOVA - Simple Main Effects (1).mp4
03:50
043 Guide 37 Mixed ANOVA - Simple Main Effects (2).mp4
06:21
044 Guide 37 Mixed ANOVA - Case of Nonsignificant Interaction.mp4
01:39
044 Guide-37-Mixed-Anova.pdf
045 Guide 38 Mann-Whitney Test - Introduction.mp4
04:04
046 Guide 38 Mann-Whitney Test - Results Interpretation.mp4
06:58
046 Guide-38-Mannwhitney.pdf
047 Guide 39 Wilcoxon and Sign Tests - Wilcoxon Test.mp4
08:02
048 Guide 39 Wilcoxon and Sign Tests - Sign Test.mp4
02:52
048 Guide-39-Wilcoxon-Sign.pdf
049 Guide 40 Kruskal-Wallis and Median Tests - Kruskal-Wallis Test.mp4
08:29
050 Guide 40 Kruskal-Wallis and Median Tests - Median Test.mp4
03:57
050 Guide-40-Kruskal-Median.pdf
051 Guide 41 Friedman Test.mp4
05:59
051 Guide-41-Friedman.pdf
052 Guide 42 McNemar Test.mp4
08:13
052 Guide-42-Mcnemar.pdf
001 Guide 43 Simple Regression - Introduction.mp4
04:29
002 Guide 43 Simple Regression - Assumption Checking (1).mp4
02:15
003 Guide 43 Simple Regression - Assumption Checking (2).mp4
07:31
004 Guide 43 Simple Regression - Results Interpretation.mp4
05:04
004 Guide-43-Simple-Reg.pdf
005 Guide 44 Multiple Regression - Introduction.mp4
02:55
006 Guide 44 Multiple Regression - Assumption Checking.mp4
12:20
007 Guide 44 Multiple Regression - Results Interpretation.mp4
05:01
007 Guide-44-Multiple-Reg.pdf
008 Guide 45 Regression with Dummy Variables.mp4
07:13
008 Guide-45-Dummy-Reg.pdf
009 Guide 46 Sequential Regression.mp4
08:48
009 Guide-46-Sequential-Reg.pdf
010 Guide 47 Binomial Regression - Introduction.mp4
05:16
011 Guide 47 Binomial Regression - Assumption Checking.mp4
02:44
012 Guide 47 Binomial Regression - Goodness-of-Fit Indicators.mp4
08:43
013 Guide 47 Binomial Regression - Coefficient Interpretation (1).mp4
03:59
014 Guide 47 Binomial Regression - Coefficient Interpretation (2).mp4
04:03
015 Guide 47 Binomial Regression - Classification Table.mp4
03:42
015 Guide-47-Binomial-Reg.pdf
016 Guide 48 Multinomial Regression - Introduction.mp4
03:41
017 Guide 48 Multinomial Regression - Assumption Checking.mp4
10:53
018 Guide 48 Multinomial Regression - Goodness-of-Fit Indicators.mp4
05:24
019 Guide 48 Multinomial Regression - Coefficient Interpretation (1).mp4
11:27
020 Guide 48 Multinomial Regression - Coefficient Interpretation (2).mp4
06:25
021 Guide 48 Multinomial Regression - Coefficient Interpretation (3).mp4
07:20
022 Guide 48 Multinomial Regression - Classification Table.mp4
03:12
022 Guide-48-Multinom-Regr.pdf
023 Guide 49 Ordinal Regression - Introduction.mp4
08:00
024 Guide 49 Ordinal Regression - Assumption Testing.mp4
06:55
025 Guide 49 Ordinal Regression - Goodness-of-Fit Indicators.mp4
05:03
026 Guide 49 Ordinal Regression - Coefficient Interpretation (1).mp4
11:19
027 Guide 49 Ordinal Regression - Coefficient Interpretation (2).mp4
01:26
028 Guide 49 Ordinal Regression - Classification Table.mp4
03:35
028 Guide-49-Ordinal-Regr.pdf
001 Guide 50 Reliability Analysis - Cronbachs Alpha.mp4
08:04
002 Guide 50 Reliability Analysis - Cohens Kappa.mp4
06:05
003 Guide 50 Reliability Analysis - Kendalls W.mp4
04:05
003 Guide-50-Reliability.pdf
004 Guide 51 Multidimensional Scaling - Introduction.mp4
04:51
005 Guide 51 Multidimensional Scaling - ALSCAL procedure (1).mp4
08:32
006 Guide 51 Multidimensional Scaling - ALSCAL procedure (2).mp4
05:29
007 Guide 51 Multidimensional Scaling - PROXSCAL procedure (1).mp4
04:28
008 Guide 51 Multidimensional Scaling - PROXSCAL procedure (2).mp4
04:34
008 Guide-51-Mds.pdf
001 Guide 52 Principal Component Analysis - Introduction.mp4
05:34
002 Guide 52 Principal Component Analysis - Running the Procedure.mp4
04:11
003 Guide 52 Principal Component Analysis - Testing For Adequacy.mp4
03:49
004 Guide 52 Principal Component Analysis - Obtaining a Final Solution.mp4
06:17
005 Guide 52 Principal Component Analysis - Interpreting the Final Solutions.mp4
04:54
006 Guide 52 Principal Component Analysis - Final Considerations.mp4
02:15
006 Guide-52-Pca.pdf
007 Guide 53 Correspondence Analysis - Introduction.mp4
03:15
008 Guide 53 Correspondence Analysis - Running the Procedure.mp4
03:15
009 Guide 53 Correspondence Analysis - Results Interpretation.mp4
03:21
010 Guide 53 Correspondence Analysis - Imposing Category Constraints.mp4
04:45
010 Guide-53-Corresp.pdf
001 Guide 54 Cluster Analysis - Introduction.mp4
01:59
002 Guide 54 Cluster Analysis - Hierarchical Cluster.mp4
14:47
003 Guide 54 Cluster Analysis - K-Means Cluster.mp4
16:02
003 Guide-54-Cluster.pdf
004 Guide 55 Discriminant Analysis - Introduction.mp4
04:35
005 Guide 55 Discriminant Analysis - Simple DA.mp4
15:08
006 Guide 55 Discriminant Analysis - Multiple DA.mp4
10:42
006 Guide-55-Discriminant.pdf
001 Guide 56 Multiple Response Analysis.mp4
10:28
001 Download Links.html
Description
SPSS data analysis made easy. Become an expert in advanced statistical analysis with SPSS.
What You'll Learn?
- perform simple operations with data: define variables, recode variables, create dummy variables, select and weight cases, split files
- built the most useful charts in SPSS: column charts, line charts, scatterplot charts, boxplot diagrams
- perform the basic data analysis procedures: Frequencies, Descriptives, Explore, Means, Crosstabs
- test the hypothesis of normality (with numeric and graphic methods)
- detect the outliers in a data series (with numeric and graphic methods)
- transform variables
- perform the main one-sample analyses: one-sample t test, binomial test, chi square for goodness of fit
- perform the tests of association: Pearson and Spearman correlation, partial correlation, chi square test for association, loglinear analysis
- execute the analyses for means comparison: t test, between-subjects ANOVA, repeated measures ANOVA, nonparametric tests (Mann-Whitney, Wilcoxon, Kruskal-Wallis etc.)
- perform the regression analysis (simple and multiple regression, sequential regression, logistic regression)
- compute and interpret various tyes of reliability indicators (Cronbach's alpha, Cohen's kappa, Kendall's W)
- use the data reduction techniques (multidimensional scaling, principal component analysis, correspondence analysis)
- use the main grouping techniques (cluster analysis, discriminant analysis)
Who is this for?
What You Need to Know?
More details
DescriptionBecome an expert in statistical analysis with the most extended SPSS course at Udemy: 146 video lectures covering about 15 hours of video!
Within a very short time you will master all the essential skills of an SPSS data analyst, from the simplest operations with data to the advanced multivariate techniques like logistic regression, multidimensional scaling or principal component analysis.
The good news – you don't need any previous experience with SPSS. If you know the very basic statistical concepts, that will do.
And you don't need to be a mathematician or a statistician to take this course (neither am I). This course was especially conceived for people who are not professional mathematicians – all the statistical procedures are presented in a simple, straightforward manner, avoiding the technical jargon and the mathematical formulas as much as possible. The formulas are used only when it is absolutely necessary, and they are thoroughly explained.
Are you a student or a PhD candidate? An academic researcher looking to improve your statistical analysis skills? Are you dreaming to get a job in the statistical analysis field some day? Are you simply passionate about quantitative analysis? This course is for you, no doubt about it.
Very important: this is not just an SPSS tutorial. It does not only show you which menu to select or which button to click in order to run some procedure. This is a hands-on statistical analysis course in the proper sense of the word.
For each statistical procedure I provide the following pieces of information:
- a short, but comprehensive description (so you understand what that technique can do for you)
- how to perform the procedure in SPSS (live)
- how to interpret the main output, so you can check your hypotheses and find the answers you need for your research)
The course contains 56 guides, presenting 56 statistical procedures, from the simplest to the most advanced (many similar courses out there don't go far beyond the basics).
The first guides are absolutely free, so you can dive into the course right now, at no risk. And don't forget that you have 30 full days to evaluate it. If you are not happy, you get your money back.
So, what do you have to lose?
Who this course is for:
- students
- PhD candidates
- academic researchers
- business researchers
- University teachers
- anyone looking for a job in the statistical analysis field
- anyone who is passionate about quantitative research
Become an expert in statistical analysis with the most extended SPSS course at Udemy: 146 video lectures covering about 15 hours of video!
Within a very short time you will master all the essential skills of an SPSS data analyst, from the simplest operations with data to the advanced multivariate techniques like logistic regression, multidimensional scaling or principal component analysis.
The good news – you don't need any previous experience with SPSS. If you know the very basic statistical concepts, that will do.
And you don't need to be a mathematician or a statistician to take this course (neither am I). This course was especially conceived for people who are not professional mathematicians – all the statistical procedures are presented in a simple, straightforward manner, avoiding the technical jargon and the mathematical formulas as much as possible. The formulas are used only when it is absolutely necessary, and they are thoroughly explained.
Are you a student or a PhD candidate? An academic researcher looking to improve your statistical analysis skills? Are you dreaming to get a job in the statistical analysis field some day? Are you simply passionate about quantitative analysis? This course is for you, no doubt about it.
Very important: this is not just an SPSS tutorial. It does not only show you which menu to select or which button to click in order to run some procedure. This is a hands-on statistical analysis course in the proper sense of the word.
For each statistical procedure I provide the following pieces of information:
- a short, but comprehensive description (so you understand what that technique can do for you)
- how to perform the procedure in SPSS (live)
- how to interpret the main output, so you can check your hypotheses and find the answers you need for your research)
The course contains 56 guides, presenting 56 statistical procedures, from the simplest to the most advanced (many similar courses out there don't go far beyond the basics).
The first guides are absolutely free, so you can dive into the course right now, at no risk. And don't forget that you have 30 full days to evaluate it. If you are not happy, you get your money back.
So, what do you have to lose?
Who this course is for:
- students
- PhD candidates
- academic researchers
- business researchers
- University teachers
- anyone looking for a job in the statistical analysis field
- anyone who is passionate about quantitative research
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Bogdan Anastasiei
Instructor's CoursesMy name is Bogdan Anastasiei and I am an assistant professor at the University of Iasi, Romania, Faculty of Economics and Business Administration. I teach Internet marketing and quantitative methods for business. I am also a business consultant. I have run quantitative risk analyses and feasibility studies for various local businesses and been implied in academic projects on risk analysis and marketing analysis. I have also written courses and articles on Internet marketing and online communication techniques. I have 24 years experience in teaching and about 15 years experience in business consulting.
Udemy
View courses UdemyStudents take courses primarily to improve job-related skills.Some courses generate credit toward technical certification. Udemy has made a special effort to attract corporate trainers seeking to create coursework for employees of their company.
- language english
- Training sessions 148
- duration 14:03:09
- English subtitles has
- Release Date 2023/12/16
