E = row total × column total / grand total, df = (r − 1)(c − 1)
Critical values (α = 0.05)
df 1: 3.841, 2: 5.991, 3: 7.815, 4: 9.488
Decision
reject H0 if χ² > χ²crit
2Practice problems
1.Normal distributionMedium
The battery lifetimes are normally distributed with mean 500 h and standard deviation 40 h. What fraction lies between 420 and 560 h? Give P as a decimal.
μ = 500σ = 40x1 = 420x2 = 560
P =
2.Normal distributionHard
The IQ scores are normally distributed with mean 100 points and standard deviation 15 points. Find the value x below which 5% of them lie (the 5th percentile).
μ = 100σ = 15P = 5%
x = points
3.Confidence intervalsMedium
A 90% confidence interval for a mean, based on 50 observations and a known σ, has a margin of error of 1.7. What is the margin of error E₂ of a 99% interval from the same data?
90%n₁ = 50E₁ = 1.799%
E₂ =
4.Confidence intervalsHard
A pilot study suggests that about 0.2 of products are defective. How many products n must be inspected so that a 99% confidence interval for the proportion has a margin of error of at most 0.05?
p ≈ 0.2E = 0.0599%
n =
5.Hypothesis tests & confidence intervalsMedium
Two teaching methods are compared. Group 1: 6 students, mean score 92.5, standard deviation 4. Group 2: 11 students, mean score 101.4, standard deviation 11. Assume equal population variances and use the pooled two-sample t test. Find the test statistic t for H₀: μ₁ = μ₂, taking the difference as x̄₁ − x̄₂ (group 1 minus group 2).
n₁ = 6x̄₁ = 92.5s₁ = 4n₂ = 11x̄₂ = 101.4s₂ = 11
t =
6.Hypothesis tests & confidence intervalsHard
A one-sided z test at α = 0.01 must detect a shift of the mean of 4 units with a power of 90%. The standard deviation is 22. Find the minimum sample size n.
The table gives 6 paired observations of x = car age in years and y = price in k€. Their sums are given. Find Pearson's correlation coefficient r from these sums.
n = 6Σx = 21Σy = 130Σx² = 91Σy² = 2860Σxy = 430
r =
8.Linear regression & correlationHard
The table gives 6 paired observations of x = load in kN and y = extension in mm. Use the least-squares line ŷ = a + b·x. Predict ŷ for x = 9.
n = 6x = 9
ŷ =
9.Chi-square testsMedium
The contingency table shows observed counts. Compute the chi-square statistic χ² for the test of independence between the row and column variables. Do not use a continuity correction.
N = 1602 × 2
χ² =
10.Chi-square testsHard
A chi-square test of independence is carried out on a contingency table with 3 rows and 6 columns (not counting the totals). Using the table, find the critical value χ²crit at significance level α = 0.01.
α = 0.01
χ²crit =
3Solutions
1.Normal distribution
Answer: P = 0.9104
Normal distribution: convert a value x to a z-score, z = (x − μ)/σ, which counts standard deviations from the mean. A z-table (or Φ(z)) gives the area to the left of z, which is P(X < x). The area to the right is 1 − Φ(z), and the area between two values is the difference of their two areas.
z-scores
z₁ = (420 − 500)/40 = −2
z₂ = (560 − 500)/40 = 1.5
Area between
P = Φ(1.5) − Φ(−2) = 0.9332 − 0.02275 = 0.9104
Answer
P = 0.9104
2.Normal distribution
Answer: x = 75.33 points
Normal distribution: convert a value x to a z-score, z = (x − μ)/σ, which counts standard deviations from the mean. A z-table (or Φ(z)) gives the area to the left of z, which is P(X < x). The area to the right is 1 − Φ(z), and the area between two values is the difference of their two areas.
z for the percentile
Φ(z) = 0.05 → z = −1.645
Back to x
x = 100 + −1.645·15 = 75.33 points
Answer
x = 75.33 points
3.Confidence intervals
Answer: E₂ = 2.662
Confidence interval for a mean: x̄ ± margin of error. With a known population σ the margin is z·σ/√n; with only the sample standard deviation s, use t with n − 1 degrees of freedom: t·s/√n. Critical values: z = 1.645 (90%), 1.96 (95%), 2.576 (99%). To get a margin E or smaller, you need n ≥ (z·σ/E)², rounded up.
Ratio of margins
E₂/E₁ = (2.576/1.645)·√(50/50) = 1.566
New margin
E₂ = 1.7·1.566 = 2.662
Answer
E₂ = 2.662
4.Confidence intervals
Answer: n = 425
Confidence interval for a proportion: p̂ ± z·√(p̂(1 − p̂)/n), where p̂ = x/n. To reach a margin E you need n ≥ z²·p(1 − p)/E², rounded up; without a prior estimate use p = 0.5, which gives the largest n.
Solve for n
n = 2.576²·0.2·0.8/0.05² = 424.7
Round up
n = 425
Answer
n = 425
5.Hypothesis tests & confidence intervals
Answer: t = −1.891
Hypothesis test: the test statistic = (estimate − value under H₀)/(standard error under H₀). The p-value is the probability, assuming H₀ is true, of a statistic at least as extreme as the one observed: the area in one tail for a one-sided H₁, twice the tail area for a two-sided H₁. Reject H₀ when p ≤ α.
Pooled variance
sp² = (5·4² + 10·11²)/15 = 86
sp = 9.274
Standard error
SE = 9.274·√(1/6 + 1/11) = 4.707
Test statistic
t = (92.5 − 101.4)/4.707 = −1.891
Answer
t = −1.891
With df = 15, the two-sided 5% critical value is 2.131; |t| is smaller, so H₀ is not rejected.
6.Hypothesis tests & confidence intervals
Answer: n = 394
Sample size for a test: to detect a true shift δ with power 1 − β in a one-sided z test at level α, the standard error must satisfy δ = (z_α + z_β)·σ/√n, so n = ((z_α + z_β)·σ/δ)², rounded up.
Solve for n
n = ((2.326 + 1.282)·22/4)² = 393.8
Round up
n = 394
Answer
n = 394
7.Linear regression & correlation
Answer: r = −0.9078
Least-squares regression: with x̄ and ȳ the means, Sxx = Σ(x − x̄)², Syy = Σ(y − ȳ)² and Sxy = Σ(x − x̄)(y − ȳ), the line ŷ = a + b·x has slope b = Sxy/Sxx and intercept a = ȳ − b·x̄, so it always passes through (x̄, ȳ). Pearson's correlation coefficient r = Sxy/√(Sxx·Syy) lies between −1 and 1; r² is the fraction of the variation in y explained by the line.
Centred sums
Sxy = 430 − 21·130/6 = −25
Sxx = 91 − 21²/6 = 17.5
Syy = 2860 − 130²/6 = 43.33
Correlation coefficient
r = −25/√(17.5·43.33) = −0.9078
Answer
r = −0.9078
8.Linear regression & correlation
Answer: ŷ = 39.42
Least-squares regression: with x̄ and ȳ the means, Sxx = Σ(x − x̄)², Syy = Σ(y − ȳ)² and Sxy = Σ(x − x̄)(y − ȳ), the line ŷ = a + b·x has slope b = Sxy/Sxx and intercept a = ȳ − b·x̄, so it always passes through (x̄, ȳ). Pearson's correlation coefficient r = Sxy/√(Sxx·Syy) lies between −1 and 1; r² is the fraction of the variation in y explained by the line.
Means
x̄ = 42/6 = 7
ȳ = 187/6 = 31.17
Sums of squares and products
Sxx = Σ(x − x̄)² = 70
Sxy = Σ(x − x̄)(y − ȳ) = 289
Regression line
b = 289/70 = 4.129
a = 31.17 − 4.129·7 = 2.267
ŷ = 2.267 + 4.129·x
Prediction
ŷ = 2.267 + 4.129·9 = 39.42
Answer
ŷ = 39.42
9.Chi-square tests
Answer: χ² = 2.667
Chi-square tests: compare observed counts O with the counts E expected under H₀ using χ² = Σ(O − E)²/E. Goodness of fit: E = n·p for each category, df = k − 1 (minus one more for each parameter estimated from the data). Independence in an r × c table: E = row total × column total / grand total, df = (r − 1)(c − 1). Reject H₀ when χ² exceeds the critical value for the chosen α.
df = 1. At α = 0.05 the critical value is 3.841, so H₀ (independence) is not rejected.
10.Chi-square tests
Answer: χ²crit = 23.21
Chi-square tests: compare observed counts O with the counts E expected under H₀ using χ² = Σ(O − E)²/E. Goodness of fit: E = n·p for each category, df = k − 1 (minus one more for each parameter estimated from the data). Independence in an r × c table: E = row total × column total / grand total, df = (r − 1)(c − 1). Reject H₀ when χ² exceeds the critical value for the chosen α.
Degrees of freedom
df = (3 − 1)·(6 − 1) = 10
Table
χ²crit(df = 10, α = 0.01) = 23.209
Answer
χ²crit = 23.209
Reject H₀ if the computed χ² is larger than this value.