Tamil Nadu HSE First Year Statistics study materials
Tamil Nadu HSE First Year Statistics study resources

Tamil Nadu HSE First Year Statistics study plan

Tamil Nadu HSE First Year Statistics · Give each week a clear focus.

8 weeks · About 6 hours per week

Week 1

Measures of Central Tendency & Scope of Statistics and Data Collection

  • Define statistics in the singular and plural sense, and list three functions and two limitations of statistics in your own words

  • Classify the following as nominal, ordinal, interval or ratio data: exam marks, blood group, ranking in a race, temperature in Celsius

  • Compute the arithmetic mean for raw data, a discrete frequency distribution and a grouped frequency distribution with class intervals, showing the step-deviation shortcut

  • Distinguish between a census and a sample survey, and state two situations where a sample survey is preferable

  • Compute the median and mode for raw data and for a grouped frequency distribution, using the standard interpolation formula for each

Your checkpoint

A one-page formula sheet covering mean, median and mode for raw, discrete and grouped data, plus 10 solved problems (two per data type) with the final answers checked against your textbook

Week 2

Measures of Central Tendency

  • Compute the geometric mean and harmonic mean for raw data and state one practical situation where each is preferred to the arithmetic mean

  • Locate the median and quartiles graphically using an ogive drawn from a cumulative frequency table

  • Derive the empirical relation among mean, median and mode for a moderately skewed distribution and apply it to find a missing value

  • Solve for a missing frequency when the mean of a grouped distribution is given

  • Compare the merits and demerits of mean, median and mode, and choose the appropriate average for a stated real-life context

Your checkpoint

A set of 15 mixed central-tendency problems solved end to end, including two missing-frequency problems and one ogive-based quartile reading, with a short written justification for each choice of average

Week 3

Measures of Dispersion

  • Compute range, quartile deviation and its coefficient for raw data and for a grouped frequency distribution

  • Compute mean deviation about the mean and about the median for raw and grouped data, and state which is smaller and why

  • Compute variance and standard deviation using the direct, assumed-mean and step-deviation methods, and verify that all three give the same answer for one data set

  • Compute the coefficient of variation for two data sets and decide which is more consistent

  • Explain why standard deviation is preferred to range and quartile deviation as a measure of dispersion

Your checkpoint

A comparison table of all dispersion measures (formula, units, merits, demerits) plus 12 solved numerical problems, including two coefficient-of-variation comparisons and one combined mean and combined standard deviation problem

Week 4

Correlation and Regression

  • Draw a scatter diagram for a given bivariate data set and describe the direction and strength of the relationship

  • Compute Karl Pearson's coefficient of correlation for raw data and for a grouped frequency distribution

  • Compute Spearman's rank correlation coefficient, including the correction for tied ranks

  • Interpret a computed correlation coefficient, and explain with an example why correlation does not imply causation

  • Derive the two lines of regression from the normal equations and compute the regression coefficients byx and bxy

Your checkpoint

A full worked correlation-and-regression report on one data set: scatter diagram, Pearson r, rank correlation with tie correction, both regression lines, the predicted value for one new observation, and a check that r equals the square root of byx times bxy

Week 5

Correlation and Regression & Skewness and Kurtosis

  • State the properties of the correlation coefficient, including its limits, its symmetry, and its independence of change of origin and scale

  • Use the relation between regression coefficients and the correlation coefficient to recover a missing value

  • Define skewness and distinguish between positive and negative skewness using a frequency curve sketch

  • Compute Karl Pearson's and Bowley's coefficients of skewness for a grouped distribution

  • Define kurtosis, distinguish leptokurtic, mesokurtic and platykurtic curves, and compute the moments-based measure for a simple data set

Your checkpoint

A 20-item mixed problem set on correlation, regression, skewness and kurtosis, scored out of 20, with every wrong item reworked and the correct method written out in a corrections log

Week 6

Probability

  • State the classical, relative-frequency and axiomatic definitions of probability, and give one limitation of each

  • Apply the addition theorem for two and three events, including the mutually exclusive and exhaustive cases

  • Apply the multiplication theorem for independent events and for conditional probability, and use Bayes' theorem on a two-stage problem

  • Solve problems using permutations and combinations, including arrangements with repeated items

  • Compute the probability of at least one success and use the complement rule to simplify a counting problem

Your checkpoint

A portfolio of 20 probability problems grouped by the rule used (addition, multiplication, conditional, Bayes, counting), each with the sample space written out explicitly before the calculation

Week 7

Random Variables and Mathematical Expectation & Sampling Techniques and Sampling Distributions

  • Distinguish between a discrete and a continuous random variable, and construct a probability distribution for a stated experiment

  • Compute the mean, variance and standard deviation of a discrete random variable from its probability mass function

  • State the properties of the binomial distribution, and compute probabilities, mean and variance for a stated n and p

  • Compare simple random sampling, stratified sampling and systematic sampling, and state one advantage and one limitation of each

  • State the central limit theorem and explain the standard error of the sample mean, including how it changes with sample size

Your checkpoint

A two-part summary sheet: one side with the expectation and variance formulas for a discrete random variable and the binomial distribution, the other with a sampling-methods comparison table, each supported by two fully solved examples

Week 8

Index Numbers & Scope of Statistics and Data Collection

  • Distinguish between a price relative and a link relative, and construct a simple aggregative price index

  • Compute Laspeyres', Paasche's and Fisher's ideal index numbers from a given price and quantity table

  • Interpret the time reversal and factor reversal tests, and check whether Fisher's ideal index satisfies both

  • Compute the cost of living index using the weighted aggregate method, and explain the limitations of index numbers

  • Complete two full-length timed practice papers under exam conditions and classify every error as conceptual, computational or careless

Your checkpoint

Two completed timed practice papers with a scored error analysis sheet listing each mistake, its cause category, and the exact revision page or formula to revisit before the exam

Milestones

Week 2: Score at least 80% on a self-made 15-question test on central tendency, including one missing-frequency and one ogive problem, without consulting notes

Week 4: Produce a correct scatter diagram, Pearson r, rank correlation with tie correction and both regression lines for an unseen data set within 45 minutes

Week 6: Solve 18 of 20 mixed probability problems correctly, with the sample space written out for each, in a single 60-minute sitting

Week 8: Score at least 75% on both timed full-length practice papers, with no conceptual errors remaining in the error analysis sheet