A researcher collected a sample of 733 US older adults and found that of their sample, 4.1% of women respondents had never been married. They want to know if the proportion of women who were never married is different than the population proportion of 7.4% of older adult women. Conduct a one-sample hypothesis test, going through all 5 steps to answer the question. One-Sample Step 1: Select the assumptions that apply Group of answer choices Random Sample of Independent Random Samples Normal Sampling Distribution Interval-ratio variable of _ Nominal variable of ___ Equal population variances Step 2: What is your research hypothesis? H1: Pu = .074; The sample has a significantly different proportion of women who were never married than the US population. H1: Pu = .041; The sample has a significantly different proportion of women who were never married than the US population. H1: Pu ≠ .074; The sample has a significantly different proportion of women who were never married than the US population. H1: Pu ≠ .041; The sample has a significantly different proportion of women who were never married than the US population. H1: Pu > .074; The sample has a significantly greater proportion of women who were never married than the US population. H1: Pu > .041; The sample has a significantly greater proportion of women who were never married than the US population. H1: Pu < .074; The sample has a significantly lower proportion of women who were never married than the US population. H1: Pu < .041; The sample has a significantly lower proportion of women who were never married than the US population. Step 3: What is the critical score? Step 4: What is your obtained score? Step 5:

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Question

A researcher collected a sample of 733 US older adults and found that of their sample, 4.1% of women respondents had never been married. They want to know if the proportion of women who were never married is different than the population proportion of 7.4% of older adult women.

Conduct a one-sample hypothesis test, going through all 5 steps to answer the question.

One-Sample

Step 1:

Select the assumptions that apply

Group of answer choices

Random Sample of __

Independent Random Samples

Normal Sampling Distribution

Interval-ratio variable of ___

Nominal variable of ___

Equal population variances

Step 2:

What is your research hypothesis?

H1: Pu = .074; The sample has a significantly different proportion of women who were never married than the US population.

H1: Pu = .041; The sample has a significantly different proportion of women who were never married than the US population.

H1: Pu ≠ .074; The sample has a significantly different proportion of women who were never married than the US population.

H1: Pu ≠ .041; The sample has a significantly different proportion of women who were never married than the US population.

H1: Pu > .074; The sample has a significantly greater proportion of women who were never married than the US population.

H1: Pu > .041; The sample has a significantly greater proportion of women who were never married than the US population.

H1: Pu < .074; The sample has a significantly lower proportion of women who were never married than the US population.

H1: Pu < .041; The sample has a significantly lower proportion of women who were never married than the US population.

Step 3:

What is the critical score?

Step 4:

What is your obtained score?

Step 5:

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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