The standard error of the difference between population proportions describes th

Question

The standard error of the difference between population proportions describes the result of subtracting one sample proportion from a second sample proportion.

T or F

If we are sampling from a normal distribution to conduct a hypothesis test, then our sampling distribution will only be normally distributed if our sample size is 30 or more.

T or F

The pooled variance is used to calculate the test statistics for comparing two population means when the population variances are assumed to be unequal.

T or F

The standard error of the difference between two means describes the variation in the difference between two sample means.

T or F

The test statistic for hypothesis tests comparing two population proportions follows the Student's t-distribution.

T or F

The level of significance represents the probability of making a Type I error.

T or F

A Type II error is known as the consumer's risk because, when it occurs in quality control settings, the customer is getting a product from a process that is not performing properly.

T or F

Reducing without increasing the sample size will cause to increase.

T or F

The hypothesis statement  is an example of a two-tail hypothesis test.

T or F

For a two-tail hypothesis test, if the absolute value of the z- or t-test statistic exceeds the absolute value of the critical value, we reject the null hypothesis.

T or F

Typically, it is very easy for a hypothesis test to accurately reject the null hypothesis when there is little difference between the hypothesized and actual population mean.

T or F

It is recommended to choose the appropriate value of alpha for the hypothesis test after the data has been collected from the sample.

T or F

The power curve plots the power values of a hypothesis test over a range of corresponding sample means.

T or F

The critical sample mean(s) is(are) the sample mean(s) that mark(s) the boundary of the rejection region.

T or F

Failing to reject the null hypothesis and accepting the null hypothesis do not refer to the same conclusion.

T or F

The hypothesis statement H: = 25 is an example of an alternative hypothesis.

T or F

The only way to reduce both and simultaneously in a hypothesis test is to increase the sample size.

T or F

Because hypothesis testing relies on a sample, we expose ourselves to the risk that our conclusions about the population will be wrong because of a sampling error.

T or F

If you are a researcher and the purpose of the hypothesis test is to prove that your findings are an improvement over the status quo, the condition that you are attempting to prove is assigned to the null hypothesis.

T or F

The value of depends on the actual value of or p.

T or F

Typical values for alpha generally range from 1% to 10% for hypothesis testing.

T or F

In a quality control setting, the sample mean provides enough evidence to determine if a process is working properly.

T or F

The median of a data set is found by adding all the values in the data set and then dividing the result by the number of observations.

T or F

When in doubt about your assumption that the population variances are equal when comparing two population means, the best strategy is to proceed with the unequal variances test.

T or F

The approximate standard error of the difference between population proportions uses the sample proportions to estimate the values of the population proportions when determining the standard deviation.

T or F

When performing a hypothesis test comparing two population means, we need to assign Population 1 to the larger sample mean and Population 2 to the smaller sample mean.

T or F

Two samples are independent of one another when the results you observe when sampling from one population have no impact on the results you observe when sampling from the second population.

T or F

The sampling distribution for the difference in means is the result of subtracting the sampling distribution for the mean of one sample from the sampling distribution for the mean of a second sample.

T or F

Explanation / Answer

Solution:

1) The standard error of the difference between population proportions describes the result of subtracting one sample proportion from a second sample proportion.:- True

Reason:- We use Standard Error of the Difference Between Population Proportions.

2.) If we are sampling from a normal distribution to conduct a hypothesis test, then our sampling distribution will only be normally distributed if our sample size is 30 or more.:- True

Reason:- We use normally distributed if our sample size is 30 or more.

3.) The pooled variance is used to calculate the test statistics for comparing two population means when the population variances are assumed to be unequal. :-True

4.) The standard error of the difference between two means describes the variation in the difference between two sample means. : True

5 .) The test statistic for hypothesis tests comparing two population proportions follows the Student's t-distribution.:-   True

Reason: We use t-test for comparing two population proportions.

6.) The level of significance represents the probability of making a Type I error.:- True

Reason: level of significance represents the type i error.

7.) A Type II error is known as the consumer's risk because, when it occurs in quality control settings, the customer is getting a product from a process that is not performing properly.: True

8.) Reducing without increasing the sample size will cause to increase.:True

Reason: if alpha is decrease, ß increase.

9. The hypothesis statement  is an example of a two-tail hypothesis test.:True

10. For a two-tail hypothesis test, if the absolute value of the z- or t-test statistic exceeds the absolute value of the critical value, we reject the null hypothesis.: True

11. Typically, it is very easy for a hypothesis test to accurately reject the null hypothesis when there is little difference between the hypothesized and actual population mean.: True

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