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
Drag z so that the shaded area under the standard normal curve, to the right of z, is 0.9591. Find z to two decimals.
A = 0.9591
z =
2.Normal distributionHard
The battery lifetimes are normally distributed with mean 500 h and standard deviation 40 h. Find the value x below which 80% of them lie (the 80th percentile).
μ = 500σ = 40P = 80%
x = h
3.Confidence intervalsMedium
A sample of 21 items has mean 89.5 and standard deviation s = 18.5. The population is roughly normal. Find the upper limit of the 99% confidence interval for the mean.
n = 21x̄ = 89.5s = 18.599%t(20) = 2.845
upper limit =
4.Confidence intervalsHard
The population standard deviation is 36. How large a sample n do you need so that a 99% confidence interval for the mean has a margin of error of at most 4?
σ = 36E = 499%
n =
5.Hypothesis tests & confidence intervalsMedium
Two teaching methods are compared. Group 1: 5 students, mean score 82.5, standard deviation 4. Group 2: 11 students, mean score 75.6, standard deviation 5. 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 = 5x̄₁ = 82.5s₁ = 4n₂ = 11x̄₂ = 75.6s₂ = 5
t =
6.Hypothesis tests & confidence intervalsHard
A one-sided z test at α = 0.05 must detect a shift of the mean of 2 units with a power of 80%. The standard deviation is 22. Find the minimum sample size n.
The table gives 6 paired observations of x = temperature in °C and y = ice creams sold. Find Pearson's correlation coefficient r.
n = 6
r =
8.Linear regression & correlationHard
The table gives 6 paired observations of x = car age in years and y = price in k€. Use the least-squares line ŷ = a + b·x. A new observation (5.5, 17) is made. Find its residual e = y − ŷ.
n = 6(5.5, 17)
e =
9.Chi-square testsMedium
The contingency table shows observed counts. For a chi-square test of independence, find the expected count E for the cell “day shift, minor”.
row total = 85column total = 51N = 159
E =
10.Chi-square testsHard
A chi-square goodness-of-fit test checks whether counts in 6 categories follow a Poisson distribution whose mean is estimated from the same data. How many degrees of freedom df does the test have?
k = 6
df =
3Solutions
1.Normal distribution
Answer: z = −1.74
From an area back to z: Φ(z) is the area to the left of z. For a left-tail area A, find z with Φ(z) = A in the table. A right-tail area A means Φ(z) = 1 − A. A central area A between −z and z leaves (1 − A)/2 in each tail, so Φ(z) = (1 + A)/2. For a value x, use x = μ + zσ.
Area to the left of z
Φ(z) = 1 − 0.9591 = 0.0409
Read the z-table backwards
Find 0.0409 inside the table and read off z.
z = −1.74
Answer
z = −1.74
2.Normal distribution
Answer: x = 533.7 h
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) = 0.8 → z = 0.8416
Back to x
x = 500 + 0.8416·40 = 533.66 h
Answer
x = 533.66 h
3.Confidence intervals
Answer: upper limit = 101
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.
Critical value
df = n − 1 = 20, t = 2.845
Margin of error
E = 2.845·18.5/√21 = 11.49
Interval
89.5 ± 11.49 → [78.01, 101]
Answer
upper limit = 101
4.Confidence intervals
Answer: n = 538
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.
Solve for n
n = (2.576·36/4)² = 537.5
Round up
A sample size is a whole number, and rounding down would make the margin too large.
n = 538
Answer
n = 538
5.Hypothesis tests & confidence intervals
Answer: t = 2.701
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 = (4·4² + 10·5²)/14 = 22.43
sp = 4.736
Standard error
SE = 4.736·√(1/5 + 1/11) = 2.554
Test statistic
t = (82.5 − 75.6)/2.554 = 2.701
Answer
t = 2.701
With df = 14, the two-sided 5% critical value is 2.145; |t| is larger, so H₀ is rejected.
6.Hypothesis tests & confidence intervals
Answer: n = 749
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 = ((1.645 + 0.842)·22/2)² = 748.4
Round up
n = 749
Answer
n = 749
7.Linear regression & correlation
Answer: r = 0.9935
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 = 132/6 = 22
ȳ = 565/6 = 94.17
Sums of squares and products
Sxx = Σ(x − x̄)² = 70
Sxy = Σ(x − x̄)(y − ȳ) = 259
Syy = Σ(y − ȳ)² = 970.8
Correlation coefficient
r = 259/√(70·970.8) = 0.9935
Answer
r = 0.9935
8.Linear regression & correlation
Answer: e = 3.429
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 = 21/6 = 3.5
ȳ = 102/6 = 17
Sums of squares and products
Sxx = Σ(x − x̄)² = 17.5
Sxy = Σ(x − x̄)(y − ȳ) = −30
Regression line
b = −30/17.5 = −1.714
a = 17 − (−1.714)·3.5 = 23
ŷ = 23 − 1.714·x
Predicted value
ŷ = 23 + (−1.714)·5.5 = 13.57
Residual
e = 17 − 13.57 = 3.429
Answer
e = 3.429
The point lies above the line.
9.Chi-square tests
Answer: E = 27.26
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.
Expected count
E = 85·51/159 = 27.26
Answer
E = 27.26
10.Chi-square tests
Answer: df = 4
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.