Statistical Methods for Psychological Research - I

By Dr. Jitendra Kumar Kushwaha | Assistant Professor at Department of Psychology, Manipur University.

Learners enrolled: 442

This is an elementary course on statistics and here we will begin with basics of statistics. The statistics are needed so that we can formulate our argument laded with substantial data input. The logic of argument may be supported by empirical data. The empirical data has scientific value because it can be retested, validated and verified. Therefore, the knowledge of statistics with its techniques of sampling as well as data collection will be very helpful tools for students.

In this course, you will learn different types of variable and their effect on each other which are captured through numerical data and interpretation of same is done statistically.

The descriptive data represented through graphs will enable students to understand various concepts of psychology more clearly along with their numerical magnitude.

Learning about probability and normal probability distributions will help you understand nature of psychological attributes and how those are distributed in populations.

Analysis of variability would enhance your learning on how much variance one variable has to explain on other variables. The correlation will also indicate degree of associations among variable and thus would propel to investigate the causation among those variables.

The completion of this course will infuse motivation and confidence on numerical interpretations of research analysis to the students.

Summary

Course Status :	Ongoing
Course Type :	Core
Duration :	15 weeks
Category :	Humanities and Social Sciences
Credit Points :	5
Level :	Undergraduate
Start Date :	15 Jan 2024
End Date :	28 Apr 2024
Enrollment Ends :	29 Feb 2024
Exam Date :	18 May 2024 IST
Exam Shift :	I

Note: This exam date is subjected to change based on seat availability. You can check final exam date on your hall ticket.

Page Visits

Course layout

WEEK 1
1	Psychological Research and Statistics: Descriptive and Inferential Statistics
2	Variables and Constants.
3	Measurement Scales: Nominal, Ordinal, Interval and Ratio
4	Organising Quantitative Data
WEEK 2
5	Constructing a Grouped Frequency distribution
6	Relative and Cumulative Frequency Distribution
7	Computation of Percentiles and Percentile Ranks
8	Usage of Microsoft Excel and SPSS
WEEK 3
9	Basic Procedures- Histogram and Frequency Polygon
10	Bar Diagram
11	Pie Chart
12	Cumulative Frequency Graph
WEEK 4
13	Factors Affecting the Shape of Graphs
14	Measures of Central Tendency-Mean
15	Measures of Central Tendency-Median
16	Median from grouped data & Mode from grouped and ungrouped data
WEEK 5
17	Properties and Relative Advantages and Disadvantages of the Mode, Median and Mean
18	Central Tendency Measures in Normal and in Skewed Distributions
19	Range: Interquartile and Semi-Interquartile Range (ungrouped data)
20	Range: Interquartile and Semi-Interquartile Range (grouped data)
WEEK 6
21	Average Deviation
22	Variance and Standard Deviation (grouped and ungrouped data)
23	Properties and Comparison of Measures of Variability
24	Nature and Properties of Normal Probability Curve (NPC)
WEEK 7
25	Applications of the Normal Probability Curve
26	Standard Normal Curve: Finding areas when the scores are known
27	Standard Normal Curve: Finding Scores when the area is known
28	Standard Scores and the Normal Curve
WEEK 8
29	Divergence from Normality (Skewness and Kurtosis)
30	Normal Curve as a Model for Real Variables and a Model for Sampling Distributions
31	Meaning of Correlation: Historical Perspective
32	Correlation: A matter of Direction and A Matter of Degree
WEEK 9
33	Pearson’s Correlation Coefficient from Deviation Scores
34	Pearson’s Correlation Coefficient from Raw Scores
35	Scatterplot of Bivariate Distributions
36	Spearman’s Rank-Order Correlation Coefficient
WEEK 10
37	Biserial r and its computation
38	The Point Biserial r Correlation Coefficient
39	Tetrachoric r and its Calculation
40	The phi Coefficient
WEEK 11
41	Partial Correlation
42	Multiple Coefficient of Correlation, R.
43	Correlation and Causation: Cautions Concerning Correlation Coefficients
44	Sampling: Need and Basic Concepts of Sampling
45	Determination of Sample Size
WEEK 12
46	Probability Sampling and its types
47	Random Sampling: Meaning, Characteristics and Relevance
48	Random Sampling: Usage of Random Number Tables
49	Random Sampling Distribution of the Mean: Introduction and Characteristics
50	Sampling Distribution of Sample Means to Determine the Probability for Different Ranges of Values of Sample Mean
WEEK 13
51	Non-Probability Sampling and its types
52	Regression and Regression Equation
53	Regression Analysis and Prediction
54	The Meaning of Statistical Inference and Related Concepts
55	The Significance of the Mean and the Median
WEEK 14
56	The Significance of Measures of Variability
57	The Significance of Percentages and the of the Correlation Coefficient
58	The Significance of the Difference between Means
59	Chi-Square- The Hypothesis of Chance
60	Computation of Chi-Square (Small Table Entries)
WEEK 15
61	The Chi-Square Test of Independence in Contingency Tables
62	Mann-Whitney U Test
63	Kendall’s Tau
64	Coefficient of Concordance
65	Median Test

Books and references

References:

Coolican, H. (2009). Research Methods and Statistics in Psychology. London and New York: Routledge. Pp. 263-265
Garrett, H. E. (2021 reprint). Statistics in Psychology and Education. New Delhi : Paragon International Publishers. Pp. 27-30.
Mangal, S.K. (2012). Statistics in Psychology & Education. 2nd Edition. New Delhi: PHI learning Pvt. Ltd. Pp. 41-43.
Kerlinger, F. N. (1973). Foundations of Behavioural Research. New York: Holt, Rinehart and Winston, Inc.
Kerlinger, F. N. (2014 reprint). Foundations of Behavioural Research. New Delhi: Surjeet Publications.
Scientific Research (2022): https://courses.lumenlearning.com/suny-hccc-research-methods/chapter/chapter-1-science-and-scientific-research/ accessed on 01-06-2022 at 13hrs.
Statistics (2022): https://www.investopedia.com/terms/s/statistics.asp. accessed on 01-06-2022 at 13hrs.

Instructor bio

Dr. Jitendra Kumar Kushwaha

Assistant Professor at Department of Psychology, Manipur University.

Dr. Jitendra Kumar Kushwaha is an Assistant Professor at Department of Psychology, Manipur University. He has eight years of teaching experience. Presently, he is teaching Research Methodology, Applied Psychometrics Advanced Statistics and Experimental Designs of Psychological Researches. He was a research fellow of DAAD, Freie University Berlin, Germany. He is well-versed in SPSS and other ICT technology.