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Advanced Statistical Analysis Using Statistical Package For Social Sciences (SPS by FINERESULTS(m): 2:57pm On Jul 01, 2020 |
FineResults Research Services invites you to training on: Topics: Advanced Statistical Analysis Using Statistical Package for Social Sciences (SPSS) Date: 19th to 23rd October 2020 Cost: USD 800 or Ksh 65000 Contacts: +254 759 285 295, training@fineresultsresearch.org Venue : FineResults Research, Nairobi, Kenya Training Centre. Enroll :Online training INTRODUCTION SPSS means Statistical Package for the Social Sciences, and it is appropriate for complex statistical data analysis of social science data. SPSS software allows for thorough data management in terms of organizing and managing data and also offers the user a lot of control. Other benefits of the software in data analysis includes it is good in data screening and cleaning, Better organization of the output in a separate window with the data editor window which avoid any data being deleted. This 5 days course intend to equip participants with advanced techniques using SPSS software. DURATION 5 days TARGET PARTICIPANTS Researchers, students, anyone who interested in enhancing his/ her data analysis skills COURSE OBJECTIVES By the end of the training, you will be able to: • Understand both descriptive and inferential statistics • Understand various data collection techniques and data processing methods • Use basic functions and navigation within Stata and SPSS software • Create and manipulate graphs and figures in SPSS software • Handle statistical data analysis tasks in SPSS software • Export the results of your analyses. TOPICS TO BE COVERED Module 1: Statistical Concepts • Statistical Concepts • Types of data • Data Structures and Types of Variables • Overview of SPSS • Working with the SPSS software (file management, editing functions, viewing options, etc) • Output Management • Basics programming of SPSS Module 2: Data Entry/Management • Entering categorical and continuous data • Defining and labeling variables • Validation and Sorting variables • Transforming, recording and computing variables • Restructuring data • Replacing missing values • Merging files and restructuring • Splitting files, Selecting cases and weighing cases • Syntax and output Module 3: Statistical Inference and Descriptive Statistics • Tests of Association • Tests of Difference • Hypothesis testing Measures of Variability and Central Tendency • Describing quantitative data • Describing qualitative data Graphics in Data Analysis • Graphing quantitative data • Graphing qualitative data • Advanced graphics options Correlation • Correlation of bivariate data • Subgroup Correlations • Scatterplots of Data by Subgroups • Overlay Scatterplots Module 4: Test statistics and tests of associations Comparing Means • One Sample t-tests • Paired Sample t-tests • Independent Samples t-tests • Comparing Means Using One-Way ANOVA • MANOVA: multivariate analysis of variance • Repeated Measures ANOVA Tests of associations • Goodness of Fit Chi Square All Categories Equal • Goodness of Fit Chi Square Categories Unequal • Chi Square for Contingency Tables • Pearson Correlation • Spearman Correlation Nonparametric Statistics • Mann-Whitney Test • Wilcoxon’s Matched Pairs Signed-Ranks Test • Kruskal-Wallis One-Way ANOVA • Friedman’s Rank Test for k Related Samples Comparing Means Using Factorial ANOVA • Factorial ANOVA Using GLM Univariate • Simple Effects Module 5: Comparing Means Using Repeated Measures ANOVA • Using GLM Repeated Measures to Calculate Repeated Measures ANOVAs • Multiple Comparisons Other topics • Multiple Regression Analysis • Logistic regression (Binary & Multinomial) • Cluster Analysis • Factor analysis NB: We are offering you a half day, fun and interactive team building event! Be part of the Training • Click HERE for the individual registration. Engage with us on Visit our face book page Visit our linkedin page Visit our twitter account |
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