A study was conducted to compare the proportion of drivers in boston and new york who wore seat belts while driving. Data were collected, and the proportion wearing seat belts in boston was 0. 581 and the proportion wearing seat belts in new york was 0. 832.

A test statistic, which can be thought of as a numerical summary of a data set that condenses the data into a single value that can be used to conduct the hypothesis test, is how a hypothesis test is commonly expressed.

The probability value, or p-value, indicates the likelihood that your data could have been true under the null hypothesis.

This is accomplished by estimating the probability of your test statistic, which is the figure obtained from a statistical analysis of your data.

So, we have to use: Ha: pB < pNY

This implies that the alternative thesis is revised as follows:

Ha: pB - pNY < 0

In contrast to the null hypothesis:

H₀: pB - pNY = 0

This is the test statistic:

z = X - μ/a

Now, pB = 0.581, pNY = 0.832.

It follows that: X = 0.581 - 0.832 = -0.251

The test for the null hypothesis is 0.

This follows to: μ = 0

Standard deviation: 0.1

This follows to: s = 0.1

Test statistic:

z = X - μ/a

z = -0.251-0/0.1

z = -2.51

Therefore, z = -2.51 is the required test statistic.

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Complete question:
A study was conducted to compare the proportion of drivers in Boston and New York who wore seat belts while driving. Data were collected, and the proportion wearing seat belts in Boston was 0.581 and the proportion wearing seat belts in New York was 0.832. Due to local laws at the time the study was conducted, it was suspected that a smaller proportion of drivers wear seat belts in Boston than New York.

Find the test statistic for this test using Ha: pB < pNY. (Use standard error = 0.1.)