Introductory Statistics: practice problems and exam questions

Descriptive statistics, probability and hypothesis testing: the statistics course that almost every degree requires.

Cram pack (PDF)Formula sheets, method steps and practice problems with full solutions, ready to print.

Topics in this course

  1. Descriptive statisticsmean and median · standard deviation · normal distributioncalculations
  2. Probabilityequally likely outcomes · counting and complements · binomial distributioncalculations
  3. Normal distributionarea in one tail · area between two values · percentilescalculations
  4. Confidence intervalsz interval · t interval · sample sizecalculations
  5. Hypothesis tests & confidence intervalsz statistic · t statistic · confidence intervalscalculations
  6. Linear regression & correlationslope and intercept · correlation coefficient · predictioncalculations

Exam tips for Introductory Statistics

  • Check whether the question is about a sample or a population.
  • Write down H₀ and H₁ before you calculate anything.
  • For probability, decide first whether the events are independent or mutually exclusive.

Worked examples

Descriptive statisticsEasy
510152025303540

Find the median M of the data: 39, 11, 3, 28, 18, 17, 40, 40, 5.

n = 9

Find M

Show hints
  1. Sort the values from smallest to largest.
  2. With an odd number of values the median is the middle one.
  3. sorted: 3, 5, 11, 17, 18, 28, 39, 40, 40.
Show the answer and the step-by-step solution

Descriptive statistics: the mean is the sum divided by n; the median is the middle value of the sorted data (the average of the two middle values when n is even). The sample standard deviation is s = √(Σ(x − x̄)²/(n − 1)). A z-score z = (x − μ)/σ says how many standard deviations a value lies from the mean.

Sort

3, 5, 11, 17, 18, 28, 39, 40, 40

Middle value

M = 18

Answer

M = 18
ProbabilityMedium
xp(x)10.1520.3530.0540.350.15μ = 2.95

For the distribution shown, find the variance Var(X) of X.

x: 1, 2, 3, 4, 5p(x): 0.15, 0.35, 0.05, 0.3, 0.15

Find Var(X)

Show hints
  1. μ = Σx·p(x) = 2.95.
  2. Then E(X²) = Σx²·p(x).
  3. Var(X) = E(X²) − μ².
Show the answer and the step-by-step solution

Discrete random variables: a probability distribution lists every value x a variable can take with its probability p(x); the probabilities are between 0 and 1 and add up to 1. The expected value (mean) is E(X) = Σx·p(x), the long-run average. The variance is Var(X) = Σ(x − μ)²·p(x) = E(X²) − μ², and the standard deviation σ = √Var(X). For a linear change Y = aX + b: E(Y) = a·E(X) + b, Var(Y) = a²·Var(X) and σY = |a|·σX; adding a constant does not change the spread.

Mean

μ = 1·0.15 + 2·0.35 + 3·0.05 + 4·0.3 + 5·0.15 = 2.95

Mean of the squares

E(X²) = 1·0.15 + 4·0.35 + 9·0.05 + 16·0.3 + 25·0.15 = 10.55

Variance

Var(X) = 10.55 − 2.95² = 1.848

Answer

Var(X) = 1.848

How practising works

  • “Practise this course” mixes problems from all its topics, like a real exam.
  • Every problem has new values, so you learn the method instead of an answer.
  • Stuck? Open a small hint first, and the full explanation only when you need it.
  • Mock exams are timed and have no hints, and you get your score and a full review at the end.

Calculators for this course

Related courses