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
−3−2−10123zshaded area to the right of z = 0.9861

Drag z so that the shaded area under the standard normal curve, to the right of z, is 0.9861. Find z to two decimals.

A = 0.9861
z =
2.Normal distributionHard
μ = 500x = ?25%

The battery lifetimes are normally distributed with mean 500 h and standard deviation 40 h. Find the value x below which 25% of them lie (the 25th percentile).

μ = 500σ = 40P = 25%
x = h
3.Confidence intervalsMedium
x̄E₁ = 2.399%, n = 25x̄E₂ = ?99%, n = 100

A 99% confidence interval for a mean, based on 25 observations and a known σ, has a margin of error of 2.3. What is the margin of error E₂ if the same study uses 100 observations instead?

99%n₁ = 25E₁ = 2.3n₂ = 100
E₂ =
4.Confidence intervalsHard
p ≈ 0.7, n = ?p̂ − Ep̂ + Ep̂E = 0.0590%

A pilot study suggests that about 0.7 of products are defective. How many products n must be inspected so that a 90% confidence interval for the proportion has a margin of error of at most 0.05?

p ≈ 0.7E = 0.0590%
n =
5.Hypothesis tests & confidence intervalsMedium
t −2.06402.064

A sample of 25 students has a mean score of 44.72 and a sample standard deviation of 12. Find the test statistic t for H₀: μ = 50.

μ₀ = 50x̄ = 44.72s = 12n = 25
t =
6.Hypothesis tests & confidence intervalsHard
z −2.57602.576

A sample of 16 measurements has mean 76.5. The population standard deviation is 4. Find the upper limit U of the 99% confidence interval for the mean.

x̄ = 76.5σ = 4n = 1699%
U =
7.Linear regression & correlationMedium
xy129223322419520xy24202530

The table gives 5 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 = 5Σx = 15Σy = 113Σx² = 55Σy² = 2615Σxy = 317
r =
8.Linear regression & correlationHard
xy12422031441451167xy2461020x = 4.5

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. Predict ŷ for x = 4.5.

n = 6x = 4.5
ŷ =
9.Chi-square testsMedium
no defectminormajorTotalday shift9141740night shift7102340Total16244080

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 = 802 × 3
χ² =
10.Chi-square testsHard
yesnoTotalline 1283260line 2334780line 3112940Total72108180dfα = 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 = 1803 × 2α = 0.01
χ² =

3Solutions

1.Normal distribution

Answer: z = −2.2

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 − 0.9861 = 0.0139

Read the z-table backwards

Find 0.0139 inside the table and read off z.

z = −2.20

Answer

z = −2.20
2.Normal distribution

Answer: x = 473 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) = 0.25 → z = −0.6745

Back to x

x = 500 + −0.6745·40 = 473.02 h

Answer

x = 473.02 h
3.Confidence intervals

Answer: E₂ = 1.15

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 = (2.576/2.576)·√(25/100) = 0.5

New margin

E₂ = 2.3·0.5 = 1.15

Answer

E₂ = 1.15
4.Confidence intervals

Answer: n = 228

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 = 1.645²·0.7·0.3/0.05² = 227.3

Round up

n = 228

Answer

n = 228
5.Hypothesis tests & confidence intervals

Answer: t = −2.2

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/√25 = 12/5 = 2.4

Test statistic

t = (44.72 − 50)/2.4 = −2.2

Answer

t = −2.2
t0.025; df = 24 = 2.064

|t| > 2.064, so H₀ is rejected at the 5% level (two-sided).

6.Hypothesis tests & confidence intervals

Answer: U = 79.08

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 = 2.576·4/√16 = 2.576

Interval limit

U = 76.5 + 2.576 = 79.08

Answer

U = 79.08
7.Linear regression & correlation

Answer: r = −0.8893

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 = 317 − 15·113/5 = −22
Sxx = 55 − 15²/5 = 10
Syy = 2615 − 113²/5 = 61.2

Correlation coefficient

r = −22/√(10·61.2) = −0.8893

Answer

r = −0.8893
8.Linear regression & correlation

Answer: ŷ = 11.8

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 = 21/6 = 3.5
ȳ = 90/6 = 15

Sums of squares and products

Sxx = Σ(x − x̄)² = 17.5
Sxy = Σ(x − x̄)(y − ȳ) = −56

Regression line

b = −56/17.5 = −3.2
a = 15 − (−3.2)·3.5 = 26.2
ŷ = 26.2 − 3.2·x

Prediction

ŷ = 26.2 + (−3.2)·4.5 = 11.8

Answer

ŷ = 11.8
9.Chi-square tests

Answer: χ² = 1.817

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

day shift: 40·16/80 = 8, 40·24/80 = 12, 40·40/80 = 20
night shift: 40·16/80 = 8, 40·24/80 = 12, 40·40/80 = 20

Chi-square statistic

χ² = (9 − 8)²/8 + (14 − 12)²/12 + (17 − 20)²/20 + (7 − 8)²/8 + (10 − 12)²/12 + (23 − 20)²/20
χ² = 1.817

Answer

χ² = 1.817

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

10.Chi-square tests

Answer: χ² = 3.767

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: 24, 36
line 2: 32, 48
line 3: 16, 24

Chi-square statistic

χ² = (28 − 24)²/24 + (32 − 36)²/36 + (33 − 32)²/32 + (47 − 48)²/48 + (11 − 16)²/16 + (29 − 24)²/24
χ² = 3.767

Decision

df = 2, χ²crit = 9.210
3.767 < 9.210

Answer

χ² = 3.767

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

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