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Programmes → Foundation course for all students of the University of Hyderabad

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Statistics for All

Course Code: FN 201  |  Credits: 3  |  Prerequisite: Basic Mathematics at high school level

Syllabus Details

  • Unit I:(Working with Data) Populations, units and variables; pictorial and graphical representation of data and their distributions — bar charts, pie charts and histograms, and how to interpret them; tabular representation; measures of central tendency and variation, five point summaries and box plots; the distribution of data and the normal distribution, with use of the normal table; data on two variables — scatter plots, correlation, two way tables, joint and marginal distributions.
  • Unit II:(Basic Probability) Random experiments, sample spaces, events, probability, conditional probability and independence, Bayes’ theorem and its uses; random variables — Bernoulli, binomial and Poisson distributions, and continuous random variables, especially the normal and its features.
  • Unit III:(Data Collection and Sampling) What makes a sample good or bad; from data to population; simple random sampling and stratified random sampling; principles of experimental design, why and how designs are made, with examples of a bad and a good design for the same problem.
  • Unit IV:(Estimation and Testing) Parameters and statistics, estimators and the qualities of a good estimator — unbiasedness, low mean square error and consistency; estimation from samples, the methods of maximum likelihood and of moments, estimation of proportions; statistical hypothesis testing, null and alternative hypotheses, type-1 and type-2 errors, tests for one and two normal distributions and for proportions, the p-value and confidence intervals.

Course Learning Objective

  1. Identify different kinds of variables — binary, ordinal and quantitative — and display data effectively in figures and tables.
  2. Compute the various measures of central tendency and spread, and explain their strengths and weaknesses.
  3. Compute probabilities of events, apply Bayes’ theorem, and compute expected values and variances of commonly used random variables.
  4. Explain what it means for a variable to be normally distributed, test this for given data using histograms and q-q plots, and explain what estimators and estimates are.
  5. Explain why statistical inference based on sampling studies and designed experiments is preferable to drawing conclusions from one’s own observations.
  1. Moore, David S., Notz, William I. and Fligner, Michael A. The Basic Practice of Statistics. W. H. Freeman, 1994
  2. Moore, David S., McCabe, George P. and Craig, Bruce A. Introduction to the Practice of Statistics. W. H. Freeman, 2009
  3. Tukey, John W. Exploratory Data Analysis. Pearson, 1977
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