Unit 1: Exploring One-Variable Data
Statistics · Unit 1 · Paper 2

Exploring One-Variable Data unit test

A test on this unit alone, marked as a percentage and a letter grade — for the test your class is actually sitting, rather than for May. Answer everything, then submit once: seeing the answer to question 3 before attempting question 4 makes the final percentage meaningless.

Paper 1Paper 2Paper 3
Each paper is built from this unit’s 21 terms and is the same for everyone, so a teacher can assign “Unit 1, Paper 2” and every student sits the identical test. Multiple choice is marked objectively; the written sections you mark yourself against the model answer and rubric.
Suggested time 37 min 34 points0/17 attempted
1

Choosing a graph type

2

Interquartile range

3

Percentile

4

Normal probability calculations

5

Effect of an outlier on mean and median

6

Standard deviation

7

Boxplot limitations

8

Normal distribution and the empirical rule

9

Why context is scored

10

Mean vs median resistance

11

Density curve

12

z-score

Short answer 1. Define or explain: Skewness direction

3 pts

Short answer 2. Define or explain: Standardizing and comparing

3 pts

Short answer 3. Define or explain: Categorical vs quantitative variables

3 pts

Short answer 4. Define or explain: Histogram vs bar chart

3 pts

Free response

10 pts

This course has no free-response prompt tagged to this unit, so one from elsewhere in the course is used. It is still worth writing — the skill transfers.

A teacher records the number of hours studied (x) and the final exam score (y) for a random sample of 24 students. Least-squares regression gives ŷ = 55 + 4.2x with r = 0.8 and SE(slope) = 0.67.

Interpret the slope in context, and calculate and interpret r² in context.

One student studied 5 hours and scored 80. Calculate and interpret the residual for this student.

State hypotheses and carry out a t-test for the slope at α = 0.05, reporting the test statistic, degrees of freedom, P-value, and a conclusion in context.

Construct a 95% confidence interval for the slope, interpret it in context, and state the conditions required for inference about a regression slope.