Statistics 2: Statistical Inference: cram pack

Formula sheets, the key method steps for every topic and 10 practice problems, with full solutions at the back.

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1Formulas and methods

Normal distribution

z-score
z = (x − μ)/σ
Below x
P(X < x) = Φ(z)
Above x
P(X > x) = 1 − Φ(z)
Between
Φ(z2) − Φ(z1)
Percentile
x = μ + z·σ

Method

  1. Convert the value to a z-score: z = (x − μ)/σ.
  2. Look up Φ(z), the area to the left of z.
  3. For the area to the right use 1 − Φ(z); for an interval subtract the two left areas.
  4. For a percentile, work backwards: find z for the area, then x = μ + z·σ.

Confidence intervals

σ known
x̄ ± z·σ/√n
σ unknown
x̄ ± t·s/√n, df = n − 1
Critical z
90%: 1.645, 95%: 1.96, 99%: 2.576
Sample size
n = (z·σ/E)², rounded up

Method

  1. Decide between z (population σ known) and t (only the sample s, with n − 1 degrees of freedom).
  2. Find the critical value for the confidence level.
  3. Margin of error: E = critical value × standard deviation/√n.
  4. Interval: x̄ ± E.

Hypothesis tests & confidence intervals

z-test for a mean
z = (x̄ − μ0)/(σ/√n)
t-test for a mean
t = (x̄ − μ0)/(s/√n), df = n − 1
Two-sided at 5%
reject H0 if |z| > 1.96
Confidence interval
x̄ ± z·σ/√n

Method

  1. State H₀ and H₁ and decide whether the test is one- or two-sided.
  2. Calculate the test statistic: (x̄ − μ₀)/(σ/√n), or with s and t.
  3. Compare with the critical value, or find the p-value.
  4. Reject H₀ if the statistic is beyond the critical value (p below α), and state the conclusion in words.

Linear regression & correlation

Sums of squares
Sxx = Σ(x − x̄)² = Σx² − (Σx)²/n, Sxy = Σxy − ΣxΣy/n
Slope
b = Sxy/Sxx
Intercept
a = ȳ − b·x̄
Correlation
r = Sxy/√(SxxSyy)
Residual
e = y − ŷ

Chi-square tests

Test statistic
χ² = Σ(O − E)²/E
Goodness of fit
E = n·p, df = k − 1 − (estimated parameters)
Independence
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
244.25257.5P = ?

The bag weights are normally distributed with mean 250 g and standard deviation 5 g. What fraction lies between 244.25 and 257.5 g? Give P as a decimal.

μ = 250σ = 5x1 = 244.25x2 = 257.5
P =
2.Normal distributionHard
μ = 500x = ?75%

The battery lifetimes are normally distributed with mean 500 h and standard deviation 40 h. Find the value x below which 75% of them lie (the 75th percentile).

μ = 500σ = 40P = 75%
x = h
3.Confidence intervalsMedium
x̄E₁ = 8.395%, n = 64x̄E₂ = ?99%, n = 64

A 95% confidence interval for a mean, based on 64 observations and a known σ, has a margin of error of 8.3. What is the margin of error E₂ of a 99% interval from the same data?

95%n₁ = 64E₁ = 8.399%
E₂ =
4.Confidence intervalsHard
σ = 37, n = ?x̄ − Ex̄ + Ex̄E = 299%

The population standard deviation is 37. 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 2?

σ = 37E = 299%
n =
5.Hypothesis tests & confidence intervalsMedium
t −2.06402.064

A sample of 25 students has a mean score of 494.4 and a sample standard deviation of 20. Find the test statistic t for H₀: μ = 500.

μ₀ = 500x̄ = 494.4s = 20n = 25
t =
6.Hypothesis tests & confidence intervalsHard
z −2.57602.576

A sample of 16 measurements has mean 96.3. The population standard deviation is 10. Find the upper limit U of the 99% confidence interval for the mean.

x̄ = 96.3σ = 10n = 1699%
U =
7.Linear regression & correlationMedium
xy252356461569677774xy24650607080

The table gives 6 paired observations of x = hours studied and y = exam score. Find Pearson's correlation coefficient r.

n = 6
r =
8.Linear regression & correlationHard
xy16591863207222792495xy206080x = 17

The table gives 5 paired observations of x = temperature in °C and y = ice creams sold. Use the least-squares line ŷ = a + b·x. Predict ŷ for x = 17.

n = 5x = 17
ŷ =
9.Chi-square testsMedium
busbikecarTotalstudents2312540staff472330100Total703535140

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 = 1402 × 3
χ² =
10.Chi-square testsHard
passfailTotalage 18–30122840age 31–50243660age 51+63440Total4298140dfα = 0.05α = 0.0113.8416.63525.9919.21037.81511.34549.48813.277511.07015.086612.59216.812714.06718.475815.50720.090916.91921.6661018.30723.209

The table shows observed counts. Test at α = 0.01 whether the two variables are independent (no continuity correction). Compute the test statistic χ², then compare it with the critical value from the table.

N = 1403 × 2α = 0.01
χ² =

3Solutions

1.Normal distribution

Answer: P = 0.8081

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 = (244.25 − 250)/5 = −1.15
z₂ = (257.5 − 250)/5 = 1.5

Area between

P = Φ(1.5) − Φ(−1.15) = 0.9332 − 0.1251 = 0.8081

Answer

P = 0.8081
2.Normal distribution

Answer: x = 527 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) = 0.75 → z = 0.6745

Back to x

x = 500 + 0.6745·40 = 526.98 h

Answer

x = 526.98 h
3.Confidence intervals

Answer: E₂ = 10.91

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 = (2.576/1.96)·√(64/64) = 1.314

New margin

E₂ = 8.3·1.314 = 10.91

Answer

E₂ = 10.91
4.Confidence intervals

Answer: n = 2272

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 = (2.576·37/2)² = 2271

Round up

A sample size is a whole number, and rounding down would make the margin too large.

n = 2272

Answer

n = 2272
5.Hypothesis tests & confidence intervals

Answer: t = −1.4

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/√25 = 20/5 = 4

Test statistic

t = (494.4 − 500)/4 = −1.4

Answer

t = −1.4
t0.025; df = 24 = 2.064

|t| < 2.064, so H₀ is not rejected at the 5% level (two-sided).

6.Hypothesis tests & confidence intervals

Answer: U = 102.7

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).

Margin of error

E = 2.576·10/√16 = 6.44

Interval limit

U = 96.3 + 6.44 = 102.7

Answer

U = 102.7
7.Linear regression & correlation

Answer: r = 0.9609

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 = 27/6 = 4.5
ȳ = 389/6 = 64.83

Sums of squares and products

Sxx = Σ(x − x̄)² = 17.5
Sxy = Σ(x − x̄)(y − ȳ) = 90.5
Syy = Σ(y − ȳ)² = 506.8

Correlation coefficient

r = 90.5/√(17.5·506.8) = 0.9609

Answer

r = 0.9609
8.Linear regression & correlation

Answer: ŷ = 60.4

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 = 100/5 = 20
ȳ = 368/5 = 73.6

Sums of squares and products

Sxx = Σ(x − x̄)² = 40
Sxy = Σ(x − x̄)(y − ȳ) = 176

Regression line

b = 176/40 = 4.4
a = 73.6 − 4.4·20 = −14.4
ŷ = −14.4 + 4.4·x

Prediction

ŷ = −14.4 + 4.4·17 = 60.4

Answer

ŷ = 60.4
9.Chi-square tests

Answer: χ² = 4.69

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 counts

students: 40·70/140 = 20, 40·35/140 = 10, 40·35/140 = 10
staff: 100·70/140 = 50, 100·35/140 = 25, 100·35/140 = 25

Chi-square statistic

χ² = (23 − 20)²/20 + (12 − 10)²/10 + (5 − 10)²/10 + (47 − 50)²/50 + (23 − 25)²/25 + (30 − 25)²/25
χ² = 4.69

Answer

χ² = 4.69

df = 2. At α = 0.05 the critical value is 5.991, so H₀ (independence) is not rejected.

10.Chi-square tests

Answer: χ² = 7.143

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 counts

age 18–30: 12, 28
age 31–50: 18, 42
age 51+: 12, 28

Chi-square statistic

χ² = (12 − 12)²/12 + (28 − 28)²/28 + (24 − 18)²/18 + (36 − 42)²/42 + (6 − 12)²/12 + (34 − 28)²/28
χ² = 7.143

Decision

df = 2, χ²crit = 9.210
7.143 < 9.210

Answer

χ² = 7.143

χ² is below the critical value, so H₀ is not rejected: there is no significant evidence of a relationship.

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