Statistics For Social Sciences
- Agricultural Sciences
- 500 level
- 3 credit units
- 156 pages
- 30 units
This course provides a clear understanding of statistics for social sciences. It covers background, roles, scope, and limitations of statistics, data collection, classification, presentation, measures of central tendency and dispersion. Also includes population, sample and sampling techniques, probability, factorial, permutation, combination, mathematical expectations, binomial, poisson, normal distributions, central limit theory, confidence interval and hypothesis testing, student's T-Test, Z distribution, F distribution, chi square analysis, correlation and regression analysis.
About this course
- Difficulty
- Intermediate
- Study hours
- 156 hours
- Maths
- Intermediate
- Content
- Theoretical, problem solving
- Practical work
- No
- Assignments
- Tutor Marked Assignments
- Final Examination
What you'll read
The real module and unit structure of AEA501, taken from the course material NOUN publishes.
One paragraph, so you can see how it reads
AEA501 · UNIT 1 GENERAL BACKGROUND AND ROLES OF STATISTICS
Statistics presents data in more comprehensive and definite form: Statistics made conclusion that are stated numerically and more convincing than conclusions stated qualitatively. For example, it is more attractive and convincing to say 85% of candidates that sat for WAEC passed in 2009 than saying most candidates that sat for WAEC in 2009 passed.
What you should be able to do
- Define and apply statistical concepts.
- Collect, classify, and present data effectively.
- Calculate measures of central tendency and dispersion.
- Apply probability theory to solve problems.
- Perform hypothesis testing and interpret results.
What it prepares you for
- Data Analyst
- Market Researcher
- Statistician
- Social Science Researcher
- Market Research
- Social Sciences
- Government
- Education
Where it gets hard
The units students slow down on, and what makes each one heavy.
- Module 7: Factorial, Permutation, Combination and Mathematical Expectations
Unit 1: Factorial and Permutations
Permutation and combination problems require strong analytical skills and careful application of formulas.
- Module 9: Central Limit Theory, Confidence Interval and Hypothesis Testing
Unit 3: Test of Hypothesis
Requires understanding of statistical inference and the ability to apply hypothesis testing procedures.
- Module 10: Student's T-Test, Z Distribution and F Distribution
Unit 1: Student's t distribution
Application of different statistical tests requires understanding of their assumptions and appropriate use cases.
A suggested way through it
13 weeks, about 42 hours in total. Yours will differ.
- Week 1Module 1: Background, Roles, Scope and Limitations of Statistics
Unit 1: General Background and Roles of Statistics · 3 hours
Define statistics and its roles.. Identify areas of application.. Discuss descriptive and inferential statistics..
- Week 2Module 1: Background, Roles, Scope and Limitations of Statistics
Unit 2: Scope of Statistics and its Limitations · 3 hours
Discuss the scope of statistics.. Explain the limitations of statistics.. Provide examples of statistical applications in various fields..
- Week 3Module 2: Data Collection, Classification and Presentation
Unit 1: Techniques of Data Collection and Data Classification · 3 hours
Differentiate between raw data and information.. Explain methods of data collection.. Outline methods of classifying data..
- Week 4Module 2: Data Collection, Classification and Presentation
Unit 2: Data Presentation and Tabulation · 3 hours
Outline methods of data presentation.. Explain tabular data presentation.. Present data graphically.. Differentiate grouped and ungrouped data..
- Week 5Module 3: Measures of Central Tendency
Unit 1: Measures of Central Tendency (The Arithmetic, Weighted, Geometric and Harmonic Mean) · 3 hours
Define types of statistical means.. Differentiate arithmetic, weighted, geometric, and harmonic means.. Solve problems related to arithmetic mean..
- Week 6Module 3: Measures of Central Tendency
Unit 2: Measures of Central Tendency (Median) · 3 hours
Determine the median from grouped and ungrouped data.. Use cumulative frequency polygon to determine the median of the distribution.. Solve problems related to median..
- Week 7Module 3: Measures of Central Tendency
Unit 3: Quartile and Percentile · 3 hours
Define and explain how quartile is calculated.. Differentiate between quartile and percentile.. Solve problems related to quartile and percentile..
- Week 8Module 3: Measures of Central Tendency
Unit 4: The Mode and Relationship Between Mean, Median and Mode · 3 hours
Define mode.. Calculate mode from grouped and ungrouped data.. Explain the relationship between mean, median, and mode.. Determine mode using frequency curve..
- Week 9Module 4: Measures of Dispersion
Unit 1: Measure of Dispersion (the Range and Mean Deviation) · 3 hours
Define range.. Calculate the range from given data.. Determine the mean deviation from a frequency distribution.. Calculate the coefficient of mean deviation..
- Week 10Module 4: Measures of Dispersion
Unit 2: Standard Deviation and Variance as a Measure of Dispersion · 3 hours
Define standard deviation.. Calculate standard deviation from grouped and ungrouped data.. Define and calculate variance.. Calculate the coefficient of variation..
- Week 11Module 5: Population, Sample and Sampling
Unit 1: Population and Sample · 3 hours
Define sample and population.. Differentiate between sample and population.. Explain the reasons for sampling..
- Week 12Module 5: Population, Sample and Sampling
Unit 2: Types of Sampling · 3 hours
Define different types of sampling.. Differentiate one sampling technique from another.. Explain each type of sampling with examples..
- Week 13Modules 1-12
Final Revision · 6 hours
Review key concepts from all modules.. Work on assignments and TMAs.. Prepare for final examination..
Preparing for the exam
- Review all module objectives and summaries.
- Practice solving problems from each unit.
- Focus on understanding the assumptions and applications of different statistical tests.
- Create a formula sheet for quick reference during the exam.
- Allocate time to revise TMAs and assignments.
Questions students ask about this course
What is AEA501 about?
This course provides a clear understanding of statistics for social sciences. It covers background, roles, scope, and limitations of statistics, data collection, classification, presentation, measures of central tendency and dispersion. Also includes population, sample and sampling techniques, probability, factorial, permutation, combination, mathematical expectations, binomial, poisson, normal distributions, central limit theory, confidence interval and hypothesis testing, student's T-Test, Z distribution, F distribution, chi square analysis, correlation and regression analysis.
How many units does AEA501 have?
AEA501, Statistics For Social Sciences, has 30 units across 12 modules, over 156 pages of course material. You can read it one unit at a time.
How many credit units is AEA501?
AEA501 carries 3 credit units, at 500 level in Agricultural Sciences.
Is AEA501 hard?
AEA501 is rated intermediate level, with intermediate mathematical content. It is mostly theoretical and problem solving work.
How long does AEA501 take to study?
About 156 hours of study, spread across its 30 units.
How is AEA501 assessed?
AEA501 is assessed by Assignments, Tutor Marked Assignments and Final Examination.
What can I do with AEA501?
Data Analyst, Market Researcher, Statistician and Social Science Researcher.