Practice Exam 1 - Math 146 - Practice (S22)

Sep 15, 2026

Uploaded by Graffin

Practice Exam #1 for Math-146 (S22) specifies a 50-minute timed assessment with a calculator-free policy (pencil/pen and paper only). The exam includes a formula sheet matching the practice exam. Coverage spans data basics, univariate and bivariate graphs and summaries (including correlation and regression), sampling and confidence intervals with standard error and CLT conditions, plus study design, confounding, and benefits of random assignment. Expected question formats include true/false, matching, homework-style multistep prompts, and StatKey lab-style output based on real data.

LanguageEnglish

CategoryExam

FormatPDF

Pages6

Reading Time15 min

AccessFree to download

General Information

Exam topics

Sampling and confidence intervals

Study design and confounding variables

Types of content to expect

Formulas

Questions

Math-146-Exam \#1-Practice (S22) General Information • You will have 50 minutes to complete Exam \#1 • You are not allowed to use anything on the exam besides a pencil/pen and paper • The ﬁrst page of the exam will be a formula sheet. It will be the exact same set of formulas given on the practice exam. Exam topics 1) Data basics-cases, variables, variable types 2) Univariate graphs and summaries-frequencies/proportions, barcharts, dotplots/histograms, shape, center (mean/median), spread (standard deviation/range/IQR), and boxplots/ﬁve number summaries 3) Bivariate graphs and summaries-contingency tables, conditional proportions, stacked barcharts, side-by-side graphs, comparative summaries, scatterplots, correlation, regression, ecological fallacy, and extrapolation 4) Sampling and conﬁdence intervals-sampling bias and sampling variability, standard deviation vs. standard error, sampling distributions, bootstrapping and bootstrap distributions, conﬁdence intervals via the 2-SE and percentile methods, conﬁdence intervals using SE formulas 5) Study design and confounding variables - observational studies vs. experiments, confounding variables, beneﬁts of random assignment Types of content to expect • 1 question consisting of several true/false statements • 1 question involving matching of deﬁnitions or methods • 1 question resembling those on the homework (ie: a prompt with several parts) • 1 question resembling those on in-class labs (ie: screenshots of StatKey output involving real data) Formulas Table of Statistical Notation: | | Population Parameter | Estimate (from sample) | | --- | --- | --- | | Mean
Standard Deviation | µσ | ¯x
s | | Proportion | p | ˆp | | Correlation | ρ | r | | Regression | β0 , β1 | b0 , b 1 | Table of Standard Error Formulas: Estimate Standard Error CLT Conditions | ˆp
¯x
ˆp1 − ˆp2
¯x1 − ¯x2
r | qp~~ ~~(1p) σ √ n qp1~~ ~~(~~ ~~1−n~~ ~~1p1~~ ~~) + p2~~ ~~(~~ ~~1−n~~ ~~2p2~~ ~~)
q σn211 + σn222 q ~~ ~~ρ22 | np ≥ 10 and n(1 − p) ≥ 10
normal population or n ≥ 30 nipi ≥ 10 and ni (1 − pi) ≥ 10 for i ∈ {1, 2} normal populations or n 1 ≥ 30 and n2 ≥ 30 normal population (both vars) or n > 30 | | --- | --- | --- | Question \#1 (true/false) For each statement (A-F), indicate whether the statement is true (T) or false (F): A) The standard error of an estimate decreases when a larger sample size is used. B) Sampling bias will decrease if a larger sample size is used. C) For the same data, a 99% conﬁdence interval estimate reﬂects a wider range of plausible values than a 90% conﬁdence interval estimate. D) The choice of explanatory and response variables matters for regression, but does not matter for correlation. E) The purpose of random assignment in a randomized experiment is to eliminate the possibility of confounding variables inﬂuencing the experiment’s outcome. F) Convenience samples are always biased, so they can never be treated as representative of a population. Question \#2 (matching) For each scenario (A-F), select the appropriate method from those described in 1-9. Not all of the options in 1-9 will be used. A) Finding an association between two categorical variables B) Describing the spread of a quantitative variable C) Describing the strength of association between two quantitative variables D) Finding an association between one categorical variable and one quantitative variable E) Describing the central tendency of a quantitative variable that is skewed to the right F) Expressing the variability in a point estimate 1) Median 2) 75th Percentile 3) Correlation coeﬃcient 4) Contingency table 5) Standard error 6) Side-by-side boxplots 7) Standard deviation 8) Stratiﬁcation 9) Simple random sampling Question \#3 (homework style) A 2015 study published in the journal SLEEP, found that just one session of cognitive behavioral therapy can help people with insomnia. In the study, 4

FAQs

What are the exam timing and allowed materials for Exam #1 (S22)?

Students have 50 minutes to complete Exam #1. Only pencil/pen and paper are allowed; no other exam resources can be used.

Which topics are included in Exam #1?

Topics cover data basics; univariate graphs and summaries; bivariate graphs and summaries including contingency tables, scatterplots, correlation, and regression; sampling and confidence intervals; and study design with confounding variables and the benefits of random assignment.

What question formats should students expect?

The exam includes true/false statements, a definitions/methods matching question, a homework-style multistep scenario prompt, and a lab-style question using screenshots of StatKey output with real data.

Sep 15, 2026

Uploaded by Graffin