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 exam scores are normally distributed with mean 65 points and standard deviation 10 points. What fraction lies between 57.5 and 80.5 points? Give P as a decimal.
μ = 65σ = 10x1 = 57.5x2 = 80.5
P =
2.Normal distributionHard
The IQ scores are normally distributed with mean 100 points and standard deviation 15 points. Drag the cut-off so the shaded bottom 40% is to the left of it. Find the cut-off x.
μ = 100 pointsσ = 15 points40%
x = points
3.Confidence intervalsMedium
A 90% confidence interval for a mean, based on 100 observations and a known σ, has a margin of error of 1.6. What is the margin of error E₂ of a 99% interval based on 25 observations?
90%n₁ = 100E₁ = 1.699%n₂ = 25
E₂ =
4.Confidence intervalsHard
The population standard deviation is 38. 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 0.5?
σ = 38E = 0.599%
n =
5.Hypothesis tests & confidence intervalsMedium
A sample of 49 students has a mean score of 494.9 and a sample standard deviation of 20. Find the test statistic t for H₀: μ = 500.
μ₀ = 500x̄ = 494.9s = 20n = 49
t =
6.Hypothesis tests & confidence intervalsHard
A one-sided z test of H₀: μ = 100 against H₁: μ < 100 is done at α = 0.10 with a sample of 64; the standard deviation is known to be 24. In reality the mean is 94.3. Find the power 1 − β of the test in percent.
μ₀ = 100μ = 94.3σ = 24n = 64α = 0.10
1 − β = %
7.Linear regression & correlationMedium
The table gives 6 paired observations of x = temperature in °C and y = ice creams sold. Find the coefficient of determination r² of the least-squares line.
n = 6
r² =
8.Linear regression & correlationHard
The table gives 5 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 = 7.
n = 5x = 7
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 × 3
χ² =
10.Chi-square testsHard
A chi-square goodness-of-fit test compares observed counts in 10 categories with fully specified expected proportions (no parameters are estimated from the data). Using the table, find the critical value χ²crit at significance level α = 0.05.
α = 0.05
χ²crit =
3Solutions
1.Normal distribution
Answer: P = 0.7128
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 = (57.5 − 65)/10 = −0.75
z₂ = (80.5 − 65)/10 = 1.55
Area between
P = Φ(1.55) − Φ(−0.75) = 0.9394 − 0.2266 = 0.7128
Answer
P = 0.7128
2.Normal distribution
Answer: x = 96.3 points
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
Φ(z) = 0.4
z from the table
z ≈ −0.25
Back to the original units
x = 100 − 0.25·15 = 96.3 points
Answer
x = 96.3 points
3.Confidence intervals
Answer: E₂ = 5.011
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)·√(100/25) = 3.132
New margin
E₂ = 1.6·3.132 = 5.011
Answer
E₂ = 5.011
4.Confidence intervals
Answer: n = 38329
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 = (2.576·38/0.5)² = 38328
Round up
A sample size is a whole number, and rounding down would make the margin too large.
n = 38329
Answer
n = 38329
5.Hypothesis tests & confidence intervals
Answer: t = −1.785
Testing a mean: the test statistic measures how many standard errors the sample mean lies from the value claimed in H₀: z = (x̄ − μ₀)/(σ/√n) when σ is known, t = (x̄ − μ₀)/(s/√n) when it is estimated from the sample. A confidence interval is x̄ ± (critical value)·(standard error).
Standard error
SE = 20/√49 = 20/7 = 2.857
Test statistic
t = (494.9 − 500)/2.857 = −1.785
Answer
t = −1.785
t0.025; df = 48 = 2.011
|t| < 2.011, so H₀ is not rejected at the 5% level (two-sided).
6.Hypothesis tests & confidence intervals
Answer: 1 − β = 73.17 %
Power of a test: power = 1 − β is the probability of rejecting H₀ when it is false. Find the cutoff x̄c from μ₀ and z_α, then compute the probability of landing beyond x̄c using the true mean: z = (x̄c − μ)/(σ/√n).
Critical sample mean
SE = 24/√64 = 3
x̄c = 100 − 1.282·3 = 96.15
z under the true mean
z = (96.15 − 94.3)/3 = 0.618
Power
power = P(Z < 0.618) = 73.17%
1 − β = 73.17%
Answer
1 − β = 73.17%
7.Linear regression & correlation
Answer: r² = 0.9646
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 = 129/6 = 21.5
ȳ = 618/6 = 103
Sums of squares and products
Sxx = Σ(x − x̄)² = 157.5
Sxy = Σ(x − x̄)(y − ȳ) = 777
Syy = Σ(y − ȳ)² = 3974
Coefficient of determination
r² = 777²/(157.5·3974) = 0.9646
Answer
r² = 0.9646
About 96.46% of the variation in y is explained by the line.
8.Linear regression & correlation
Answer: ŷ = 23.95
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 = 30/5 = 6
ȳ = 105/5 = 21
Sums of squares and products
Sxx = Σ(x − x̄)² = 40
Sxy = Σ(x − x̄)(y − ȳ) = 118
Regression line
b = 118/40 = 2.95
a = 21 − 2.95·6 = 3.3
ŷ = 3.3 + 2.95·x
Prediction
ŷ = 3.3 + 2.95·7 = 23.95
Answer
ŷ = 23.95
9.Chi-square tests
Answer: χ² = 11.39
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 = 2. At α = 0.05 the critical value is 5.991, so H₀ (independence) is rejected.
10.Chi-square tests
Answer: χ²crit = 16.92
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 = 10 − 1 = 9
Table
χ²crit(df = 9, α = 0.05) = 16.919
Answer
χ²crit = 16.919
Reject H₀ if the computed χ² is larger than this value.