# Statistical Methods for Psychological Research-I

By Dr. Jitendra Kumar Kushwaha   |   Assistant Professor at Department of Psychology, Manipur University.
Learners enrolled: 622
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 : 12 weeks Start Date : 23 Jan 2023 End Date : 16 Apr 2023 Exam Date : Enrollment Ends : 15 Mar 2023 Category : Humanities and Social Sciences Credit Points : 5 Level : Undergraduate

### Course layout

WEEEK 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
1. Constructing a Grouped Frequency distribution
2.  Relative and Cumulative Frequency Distribution
3. Computation of Percentiles and Percentile Ranks
4. Usage of Microsoft Excel and SPSS
WEEK 3
1. Basic Procedures- Histogram and Frequency Polygon
2. Bar Diagram
3. Pie Chart
4. Cumulative Frequency Graph
WEEK 4
1. Factors Affecting the Shape of Graphs
2. Mode (grouped and ungrouped data)
3. Mean (grouped and ungrouped data)
4. Median (grouped and ungrouped data)
WEEK 5
1. Properties and Relative Advantages and Disadvantages of the Mode, Median and Mean
2. Central Tendency Measures in Normal and in Skewed Distributions
3. Range: Interquartile and Semi-Interquartile Range (ungrouped data)
4. Range: Interquartile and Semi-Interquartile Range (grouped data)
WEEK 6
1. Average Deviation
2. Variance and Standard Deviation (grouped and ungrouped data)
3. Properties and Comparison of Measures of Variability
4. Nature and Properties of Normal Probability Curve (NPC)
WEEK 7
1. Standard Normal Curve: Finding areas when the scores are known
2. Standard Normal Curve: Finding Scores when the area is known
3. Standard Scores and the Normal Curve
4. Divergence from Normality (Skewness and Kurtosis)
WEEK 8
1. Normal Curve as a Model for Real Variables and a Model for Sampling Distributions
2. Meaning of Correlation: Historical Perspective
3. Correlation: A matter of Direction and A Matter of Degree
4. Pearson’s Correlation Coefficient from Deviation Scores
WEEK 9
1. Pearson’s Correlation Coefficient from Raw Scores
2. Scatterplot of Bivariate Distributions
3. Spearman’s Rank-Order Correlation Coefficient
4. Biserial r and its computation
WEEK 10
1. The Point Biserial r Correlation Coefficient
2. Tetrachoric r and its Calculation
3. The phi Coefficient
4. Partial Correlation
WEEK 11
1. Multiple Coefficient of Correlation, R.
2. Correlation and Causation: Cautions Concerning Correlation Coefficients
3. Sampling: Need and Basic Concepts of Sampling
4. Determination of Sample Size
5. Probability Sampling and its types
WEEK 12
1. Random Sampling: Meaning, Characteristics and Relevance
2. Random Sampling: Usage of Random Number Tables
3. Random Sampling Distribution of the Mean: Introduction and Characteristics
4. Sampling Distribution of Sample Means to Determine the Probability for Different Ranges of Values of Sample Mean;
5. Non-Probability Sampling and its types

### Books and references

References:
1. Coolican, H. (2009). Research Methods and Statistics in Psychology. London and New York: Routledge.  Pp. 263-265
2. Garrett, H. E. (2021 reprint). Statistics in Psychology and Education. New Delhi : Paragon International Publishers. Pp. 27-30.
3. Mangal, S.K. (2012). Statistics  in Psychology & Education. 2nd Edition. New Delhi: PHI learning Pvt. Ltd. Pp. 41-43.
4. Kerlinger, F. N. (1973). Foundations of Behavioural Research. New York: Holt, Rinehart and Winston, Inc.
5. Kerlinger, F. N. (2014 reprint). Foundations of Behavioural Research. New Delhi: Surjeet Publications.
6. 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.
7. Statistics (2022): https://www.investopedia.com/terms/s/statistics.asp. accessed on 01-06-2022 at 13hrs.

### 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.

### Course certificate

30% for in-course Assessment & 70% for end-term Proctored Exam.