
Assumptions behind Inference Testing
Authored by Theodore Cann
Mathematics
12th Grade
CCSS covered
Used 3+ times

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10 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is not an assumption behind the one population mean z-test?
Simple random samples
𝜎 is known
Approximately normal distribution or n >30
Approximately normal distribution or n <30
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is not an assumption behind the one population mean t-test?
Simple random samples
𝜎 is known
𝜎 is not known
Approximately normal distribution or n <30
3.
MULTIPLE SELECT QUESTION
45 sec • 1 pt
Which of the following are assumptions behind the one population proportion z-test? Check all that apply.
Voluntary Response sample
Fixed number of trials.
Fixed Probability.
Dependent Events.
𝑛𝑝≥5, 𝑛(1−𝑝)≥5
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
The assumptions are:
1) Sample data consists of measures taken before and after treatment is imposed.
2) Sample comes from a population that is normally distributed.
3) Both samples are simple random.
4) sigma is unknown
The method of inference used is most likely a:
One-way Chi-square
Linear Regression t-interval
Matched Pairs t-interval
Independent Samples t-test
Tags
CCSS.HSS.ID.A.4
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Both variables are reasonably normally distributed, the relationship between them is linear, the range of both variables is appropriate to the research question. These are the assumptions for which hypothesis test?
Linear regression t-test
Two population means - independent samples
Two population proportions
Two population means - Matched Pairs
None of these
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is not an assumption behind the one-way chi-square
test?
Simple random samples
Testing for homogeneity
Approximately normal distribution
Testing for independence
Testing for goodness of fit
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is not an assumption behind the two-way chi-square
test?
Simple random samples
Testing for homogeneity
Approximately normal distribution
Testing for independence
Testing for goodness of fit
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