Hypothesis Testing and Z Values

The video tutorial explains hypothesis testing, focusing on null and alternative hypotheses. It covers critical values, confidence levels, and how to calculate test statistics using z and t distributions. The tutorial also discusses when to use normal vs t distributions based on sample size and standard deviation knowledge. Finally, it addresses testing population proportions using specific formulas.

What is the null hypothesis in hypothesis testing?

• The hypothesis that the mean is different from a specified value.

• The hypothesis that the mean is less than a specified value.

• The hypothesis that the mean is equal to a specified value.

• The hypothesis that the mean is greater than a specified value.

What is the rejection region in hypothesis testing?

• The area where the null hypothesis is accepted.

• The area where the null hypothesis is rejected.

• The area where the alternative hypothesis is rejected.

• The area where the alternative hypothesis is accepted.

What are critical values used for in hypothesis testing?

• To calculate the mean of the sample.

• To find the standard deviation of the population.

• To separate the rejection and fail to reject regions.

• To determine the sample size.

In hypothesis testing, what does a 95% confidence level imply?

• The critical values are set to 1.96 on both sides.

• The probability of rejecting the null hypothesis is 95%.

• The sample mean is within 95% of the population mean.

• The probability of not rejecting the null hypothesis is 95%.

How do you decide to reject the null hypothesis using the calculated z value?

• If the calculated z value is equal to the critical value.

• If the calculated z value is less than zero.

• If the calculated z value is in the rejection region.

• If the calculated z value is in the fail to reject region.

When should you use the t distribution in hypothesis testing?

• When the sample size is greater than 30 and the population standard deviation is known.

• When the sample size is less than 30 and the population standard deviation is unknown.

• When the sample size is greater than 30 and the population standard deviation is unknown.

• When the sample size is less than 30 and the population standard deviation is known.

What formula is used to calculate the z value when the population standard deviation is known?

• Sample mean plus population mean divided by population standard deviation over the square root of n.

• Sample mean minus population mean divided by population standard deviation over the square root of n.

• Sample mean minus population mean divided by sample standard deviation over the square root of n.

• Sample mean plus population mean divided by sample standard deviation over the square root of n.

What is the significance of using sigma instead of s in hypothesis testing?

• Sigma is used when the sample size is small.

• Sigma is used when the sample standard deviation is unknown.

• Sigma is used when the population standard deviation is known.

• Sigma is used when the sample size is large.

What is the formula for calculating the z value when dealing with population proportions?

• Sample proportion plus population proportion divided by the square root of n over pq.

• Sample proportion minus population proportion divided by the square root of n over pq.

• Sample proportion plus population proportion divided by the square root of pq over n.

• Sample proportion minus population proportion divided by the square root of pq over n.

What does 'q' represent in the formula for calculating z value with proportions?

• The population proportion.

• One minus the sample proportion.

• The sample proportion.

• One minus the population proportion.