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FSS211

Social Science Statistics

This course introduces students to the fundamental concepts and applications of social science statistics. It covers descriptive statistics, including measures of central tendency and dispersion, as well as data collection and presentation methods. Students will also learn about probability, sampling, hypothesis testing, correlation, and regression analysis. The course aims to equip social science students with the statistical knowledge necessary for analyzing social issues and making informed decisions.

About this course

Difficulty
Intermediate
Study hours
156 hours
Maths
Intermediate
Content
Theoretical, problem solving
Practical work
Yes
How it is assessed
  • Assignments
  • Tutor marked assessments
  • Final examination

One paragraph, so you can see how it reads

FSS211 · Module 1: Introduction, Concepts And Methods Of Statistics

Inferential statistics, going by the definition from the SAGE dictionary, is that branch of statistics which deals with generalization from samples to Differentiate between statistics as numeric values and statistics as a field of study.

What you should be able to do

  1. Discuss the definitions, meaning, types and importance of statistics.
  2. Elucidate the several approaches to data collection, their merits and limitations.
  3. Discuss variables, types, measurement and their relationship.
  4. Understand the classification of data.
  5. Present data using tables, graphs and charts.
  6. Analyze measures of central tendencies and dispersion and their usefulness in statistics.
  7. Explain the probability theory.
  8. Understand correlation and its application.
  9. Understand the nature, meaning and importance of regression analysis and its application.

What it prepares you for

Careers
  • Data Analyst
  • Market Researcher
  • Social Science Researcher
  • Policy Analyst
  • Statistician
Where it is applied
  • Government
  • Healthcare
  • Education
  • Market Research
  • Social Services

Where it gets hard

The units students slow down on, and what makes each one heavy.

  • Module 3: Inferential Statistics

    Unit 2: Hypothesis and Significance Testing

    Requires understanding of statistical distributions and application of critical values from statistical tables.

  • Module 3: Inferential Statistics

    Unit 3: Correlation

    Requires understanding of the relationship between variables and the ability to interpret correlation coefficients.

  • Module 3: Inferential Statistics

    Unit 4: Regression Analysis

    Requires understanding of the assumptions of linear regression and the ability to interpret regression coefficients.

A suggested way through it

Suggested

13 weeks, about 45 hours in total. Yours will differ.

  1. Week 1Module 1: Introduction, Concepts And Methods Of Statistics
    • Unit 1: Meaning, Types, Concepts and Importance of Statistics · 3 hours

      Define statistics, its types, and importance.. Differentiate between descriptive and inferential statistics.. Understand basic statistical concepts like population, sample, and variable..

  2. Week 2Module 1: Introduction, Concepts And Methods Of Statistics
    • Unit 2: Meaning Types and Classification of Statistical Symbols · 3 hours

      Identify and explain alphabetical, Greek, and mathematical symbols.. Understand the functions of connectives and operators.. Practice using statistical symbols in calculations..

  3. Week 3Module 1: Introduction, Concepts And Methods Of Statistics
    • Unit 3: Variables and their Measurement · 3 hours

      Define variables and their measurements.. Classify variables as quantitative or qualitative.. Differentiate between independent and dependent variables.. Understand nominal, ordinal, interval, and ratio scales..

  4. Week 4Module 2: Descriptive Statistics And Probability
    • Unit 1: Measure of Central Tendency and Dispersion · 3 hours

      Calculate the mean, median, and mode for a given data set.. Understand the strengths and weaknesses of each measure.. Calculate the range, variance, and standard deviation.. Identify outliers..

  5. Week 5Module 2: Descriptive Statistics And Probability
    • Unit 2: Data Collection and Presentation · 3 hours

      Define data and its types.. Understand primary and secondary data collection methods.. Present data using tables, frequency distributions, histograms, polygons, bar charts, and pie charts..

  6. Week 6Module 2: Descriptive Statistics And Probability
    • Unit 3: Probability · 3 hours

      Understand probability theory.. Differentiate between discrete and continuous probability.. Solve probability problems using binomial and Poisson distributions..

  7. Week 7Module 3: Inferential Statistics
    • Unit 1: Sampling · 3 hours

      Define sampling and its basic concepts.. Understand probability and non-probability sampling methods.. Differentiate between sampling with and without replacement.. Understand sampling error..

  8. Week 8Module 3: Inferential Statistics
    • Unit 2: Hypothesis and Significance Testing · 3 hours

      Define hypothesis and significance testing.. Understand substantive and null hypotheses.. Identify Type I and Type II errors.. Understand the level of significance and critical region..

  9. Week 9Module 3: Inferential Statistics
    • Unit 2: Hypothesis and Significance Testing · 3 hours

      Understand one-tailed and two-tailed tests.. Calculate degrees of freedom.. Perform hypothesis tests using Chi-Square and t-tests..

  10. Week 10Module 3: Inferential Statistics
    • Unit 3: Correlation · 3 hours

      Define correlation and its types.. Calculate correlation using Pearson and Spearman rank correlations.. Understand the properties of Pearson correlation.. Calculate the coefficient of determination..

  11. Week 11Module 3: Inferential Statistics
    • Unit 4: Regression Analysis · 3 hours

      Define regression analysis and its uses.. Understand types of regression analysis.. Identify possible regression lines.. Understand assumptions of linear regression analysis.. Apply the least squares method..

  12. Week 12Course Review
    • Final Revision and TMA Preparation · 6 hours

      Review all modules and units.. Work on assignments and TMAs.. Practice statistical calculations and problem-solving..

  13. Week 13Course Review
    • Final Revision and TMA Preparation · 6 hours

      Complete all assignments and TMAs.. Focus on areas of weakness.. Practice exam questions..

Preparing for the exam

What to do
  • Create a study schedule allocating specific time for each unit.
  • Practice solving statistical problems from the self-assessment exercises.
  • Focus on understanding the concepts of hypothesis testing and significance levels.
  • Review the formulas for calculating correlation and regression coefficients.
  • Create concept maps linking Units 3-5 database concepts

Questions students ask about this course

What is FSS211 about?

This course introduces students to the fundamental concepts and applications of social science statistics. It covers descriptive statistics, including measures of central tendency and dispersion, as well as data collection and presentation methods. Students will also learn about probability, sampling, hypothesis testing, correlation, and regression analysis. The course aims to equip social science students with the statistical knowledge necessary for analyzing social issues and making informed decisions.

How many units does FSS211 have?

FSS211, Social Science Statistics, has 10 units across 3 modules, over 128 pages of course material. You can read it one unit at a time.

Is FSS211 hard?

FSS211 is rated intermediate level, with intermediate mathematical content. It is mostly theoretical and problem solving work, and it has a practical component.

How long does FSS211 take to study?

About 156 hours of study, spread across its 10 units.

How is FSS211 assessed?

FSS211 is assessed by assignments, tutor marked assessments and final examination.

What can I do with FSS211?

Data Analyst, Market Researcher, Social Science Researcher, Policy Analyst and Statistician.

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