Description
This course delves into the various fundamental statistical concepts and methods used to describe and analyze data. This will cover the major concepts of both descriptive and inferential statistics so that the participants can grasp the theoretical and mathematical concepts in both branches of statistics. This will also emphasize the applied aspects of Statistics, especially towards research in the social sciences. The course is mainly designed for newbies in the field of Statistics and also for those wanting to refresh their basic knowledge in Statitsics.
Course Outline
MODULE 1: INTRODUCTION TO STATISTICS
Lesson 1: Basic Statistical Concepts
1.1 What is Statistics?
1.2 Branches of Statistics
1.3 Population vs Sample
1.4 Sampling
1.5 Data Collection
1.6 Reliability and Validity
1.7 Biases and Errors
Lesson 2: Variables, Data, and Datasets
2.1 Variables, Data, and Datasets
2.2 Data Types
2.3 Levels of Measurement
MODULE 2: DESCRIPTIVE STATISTICS
Lesson 3: Descriptive Measures
3.1 Descriptive Statistics
3.2 Measures of Central Tendency
3.3 Measures of Dispersion
3.4 Measures of Position
3.5 Measures of Shape
Lesson 4: Graphs and Charts
4.1 Pie Chart
4.2 Bar Graph
4.3 Time Chart
4.4 Histogram
4.5 Box and Whisker Plots
4.6 Steam and Leaf Plot
MODULE 3: INFERRENTIAL STATISTICS
Lesson 5: Parametric and Non-parametric Analyses
5.1 Hypothesis Testing
5.2 Parametric vs Non-parametric Data Analysis
5.3 Testing for Normality
5.4 Testing for Homogeneity of Variance
5.5 Testing Randomness
5.6 Identifying Outliers
5.7 The Parametric and Non-parametric tests
Lesson 6: Parametric Analysis
6.1 z-test
6.2 One Sample T-test
6.3 Dependent Samples T-test
6.4 Independent Samples T-test
6.5 Analysis of Variance
Lesson 7: Non-parametric Analysis
7.1 Wilcoxon Signed Rank test
7.2 One-sample Wilcoxon Signed Rank test
7.3 Mann-Whitney U test
7.4 Kruskal Wallis test
7.5 Friedman test
MODULE 4: CORRELATION AND REGRESSION ANALYSIS
8.1 Correlation Analysis
8.2 Types of Correlation Analyses
8.3 Pearson Correlation
8.4 Spearman Correlation
8.5 Kendall Tau
8.6 Chi-square test
Lesson 9: Regression Analysis
9.1 Regression Analysis
9.2 Simple Linear Regression
9.3 Multiple Linear Regression
9.4 Regression Diagnostics
References:
Books:
1. Kent State University Libraries (2017) SPSS tutorials. Retrieved from https://libguides.library.kent.edu/SPSS/
2. McCormick, K., Salcedo, J., Poh, A. (2015) SPSS Statistics for Dummies 3rd Edition. John Wiley & Sons, Inc., Hoboken, New Jersey
3. Wahl, M. (2013) Crash Course on Basic Statistics. University of New York at Stony Brook
4. Raykov, T., Marcoulides, G. (2012) Basic Statistics: An Introduction with R. Rowman & Littlefield Publishers, Inc.
5. Beginning Statistics (2012) Retrieved from https://2012books.lardbucket.org/books/beginning-statistics/
6. Kerns, G. J. (2011) Introduction to Probability and Statistics Using R 1st Edition.
7. Manikandan, S. (2011) Measures of central tendency: The mean. J Pharmacol Pharmacother. doi: 10.4103/0976-500X.81920. PMID: 21772786; PMCID: PMC3127352.
8. Rumsey, D. (2010) Statistics Essentials for Dummies. Wiley Publishing Inc.
9. Ho, R. (2006) Handbook of Univariate and Multivariate Data Analysis and Interpretation with SPSS. Chapman and Hall/CRC
10. Sundar Rao P.S., Richard J. (2006) Introduction to biostatistics and research methods 4th Edition. New Delhi, India: Prentice Hall of India Pvt Ltd.
11. Gujarati, D. (2003) Basic Econometrics Fourth Edition. McGraw-Hill
12. Weiss, N.A. (1999) Introductory Statistics. Addison Wesley
Others (Web/Online):
1. https://www.cuemath.com/data/
2. https://byjus.com/maths/
Other Resources:
Do you want to further enrich your learning? You may also enroll in the Google Classroom of this course to assess your progress and learning AT NO COST. Feel free to e-mail me!
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