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
240.25260P = ?

The bag weights are normally distributed with mean 250 g and standard deviation 5 g. What fraction lies between 240.25 and 260 g? Give P as a decimal.

μ = 250σ = 5x1 = 240.25x2 = 260
P =
2.Normal distributionHard
μ = 65x = ?5%

The exam scores are normally distributed with mean 65 points and standard deviation 10 points. Find the value x below which 5% of them lie (the 5th percentile).

μ = 65σ = 10P = 5%
x = points
3.Confidence intervalsMedium
n = 25, s = 17.5LUx̄ = 86.5E = ?90%

A sample of 25 items has mean 86.5 and standard deviation s = 17.5. The population is roughly normal. Find the margin of error E of a 90% confidence interval for the mean.

n = 25x̄ = 86.5s = 17.590%t(24) = 1.711
E =
4.Confidence intervalsHard
σ = 14, n = ?x̄ − Ex̄ + Ex̄E = 299%

The population standard deviation is 14. 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 = 14E = 299%
n =
5.Hypothesis tests & confidence intervalsMedium
t −1.99801.998

A sample of 64 students has a mean score of 97.3 and a sample standard deviation of 12. Find the test statistic t for H₀: μ = 100.

μ₀ = 100x̄ = 97.3s = 12n = 64
t =
6.Hypothesis tests & confidence intervalsHard
−1.961.96z = ?

In a trial, 72 of 120 patients on treatment A recover, and 55 of 100 patients on treatment B. Using the pooled proportion, find the test statistic z for H₀: p₁ = p₂.

x₁ = 72n₁ = 120x₂ = 55n₂ = 100
z =
7.Linear regression & correlationMedium
xy156262360467572681xy246607080

The table gives 6 paired observations of x = hours studied and y = exam score. Their sums are given. Find Pearson's correlation coefficient r from these sums.

n = 6Σx = 21Σy = 398Σx² = 91Σy² = 26814Σxy = 1474
r =
8.Linear regression & correlationHard
xy16861899201132212824126xy20100120x = 23

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 = 23.

n = 5x = 23
ŷ =
9.Chi-square testsMedium
lowmediumhighTotalurban212950100rural2113640Total424256140

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
yesnoTotalline 1503080line 2471360line 353760Total15050200dfα = 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 = 0.05 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 = 2003 × 2α = 0.05
χ² =

3Solutions

1.Normal distribution

Answer: P = 0.9517

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 = (240.25 − 250)/5 = −1.95
z₂ = (260 − 250)/5 = 2

Area between

P = Φ(2) − Φ(−1.95) = 0.9772 − 0.02559 = 0.9517

Answer

P = 0.9517
2.Normal distribution

Answer: x = 48.55 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 = 65 + −1.645·10 = 48.55 points

Answer

x = 48.55 points
3.Confidence intervals

Answer: E = 5.989

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 = 24, t = 1.711

Margin of error

E = 1.711·17.5/√25 = 5.989

Answer

E = 5.989
4.Confidence intervals

Answer: n = 326

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 = (2.576·14/2)² = 325.2

Round up

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

n = 326

Answer

n = 326
5.Hypothesis tests & confidence intervals

Answer: t = −1.8

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 = 12/√64 = 12/8 = 1.5

Test statistic

t = (97.3 − 100)/1.5 = −1.8

Answer

t = −1.8
t0.025; df = 63 = 1.998

|t| < 1.998, so H₀ is not rejected at the 5% level (two-sided).

6.Hypothesis tests & confidence intervals

Answer: z = 0.7475

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.

Sample proportions

p̂₁ = 72/120 = 0.6
p̂₂ = 55/100 = 0.55
p̂ = 127/220 = 0.5773

Standard error under H₀

SE = √(0.5773·0.4227·(1/120 + 1/100)) = 0.06689

Test statistic

z = (0.6 − 0.55)/0.06689 = 0.7475

Answer

z = 0.7475

|z| < 1.96, so H₀ is not rejected at the 5% level (two-sided).

7.Linear regression & correlation

Answer: r = 0.9524

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 = 1474 − 21·398/6 = 81
Sxx = 91 − 21²/6 = 17.5
Syy = 26814 − 398²/6 = 413.3

Correlation coefficient

r = 81/√(17.5·413.3) = 0.9524

Answer

r = 0.9524
8.Linear regression & correlation

Answer: ŷ = 126.8

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 = 552/5 = 110.4

Sums of squares and products

Sxx = Σ(x − x̄)² = 40
Sxy = Σ(x − x̄)(y − ȳ) = 218

Regression line

b = 218/40 = 5.45
a = 110.4 − 5.45·20 = 1.4
ŷ = 1.4 + 5.45·x

Prediction

ŷ = 1.4 + 5.45·23 = 126.8

Answer

ŷ = 126.8
9.Chi-square tests

Answer: χ² = 18.32

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

urban: 100·42/140 = 30, 100·42/140 = 30, 100·56/140 = 40
rural: 40·42/140 = 12, 40·42/140 = 12, 40·56/140 = 16

Chi-square statistic

χ² = (21 − 30)²/30 + (29 − 30)²/30 + (50 − 40)²/40 + (21 − 12)²/12 + (13 − 12)²/12 + (6 − 16)²/16
χ² = 18.32

Answer

χ² = 18.32

df = 2. At α = 0.05 the critical value is 5.991, so H₀ (independence) is rejected.

10.Chi-square tests

Answer: χ² = 12.71

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

line 1: 60, 20
line 2: 45, 15
line 3: 45, 15

Chi-square statistic

χ² = (50 − 60)²/60 + (30 − 20)²/20 + (47 − 45)²/45 + (13 − 15)²/15 + (53 − 45)²/45 + (7 − 15)²/15
χ² = 12.71

Decision

df = 2, χ²crit = 5.991
12.71 > 5.991

Answer

χ² = 12.71

χ² is above the critical value, so H₀ is rejected: the variables appear to be related.

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