HCD 300 Homework and Participation 7

True or False, power is the ability of a study to find a difference if it actually exists.

True

A type I error is made when - "the null hypothesis is rejected when it is actually true " - the null hypothesis is not rejected when it is false - the alternative hypothesis is not rejected when it is false - the alternative hypothesis is not rejected when it is true

"the null hypothesis is rejected when it is actually true "

The average BMI for a sample of 10 preschoolers is 16.1, with a standard deviation of 1.4. What is the 90% confidence interval for the BMI of all preschoolers? - (15.1, 17.10) - (14.66, 17.54) - (14.32, 18.23) - (15.29, 16.91)

(15.29, 16.91)

The average BMI for a sample of 10 students is 16.1, with a standard deviation of 1.4. What is the 90% confidence interval for the BMI of all students? - (15.29, 16.91) - (14.66, 17.54) - (15.1, 17.10) - (14.32, 18.23)

(15.29, 16.91) - The interval/ratio formula using the Z score is used for sample sizes greater than 30. The interval/ratio formula using the T score is used for samples less than 30. The proportion formula is used for samples with proportions. - use the third formula and input "=1.833*(1.4/(SQRT(10))" - then subtract/add mean (16.1) by that number

If in a sample of 355 adult males, we have a mean total cholesterol level of 185 mg, with s = 16. What is the 95% confidence interval for mean total cholesterol level of all males? - (181.45, 188.37) - (183.34, 186.66) - (183.6, 186.4) - (182.8, 187.2)

(183.34, 186.66)

If in a sample of 355 adult females, we have a mean total cholesterol level of 185 mg, with s = 16. What is the 95% confidence interval for mean total cholesterol level of all females? - (181.45, 188.37) - (182.8, 187.2) - (183.34, 186.66) - (183.6, 186.4)

(183.34, 186.66) - use first equation, input "=significance.norm(0.05,16,355)" - then subtract/add mean by the number you get

In a randomly selected sample of 500 Phoenix residents, 445 supported mandatory sick leave for food handlers. Legislators want to be very confident that voters will support this issue before drafting a bill. What is the 99% confidence interval for the percentage of Phoenix residents who support mandatory sick leave for food handlers? - There is not enough information to determine CI - (85.4%, 92.6%) - (86.7%, 91.3%) - (86.26%, 91.74%)

(85.4%, 92.6%)

In a randomly selected sample of 500 parents, 445 supported 4 day school weeks for their children. What is the 99% confidence interval for the percentage of parents who support 4 day school weeks? - (86.26%, 91.74%) - (84.3%, 92.2%) - (86.7%, 91.3%) - (85.4%, 92.6%)

(85.4%, 92.6%) - use proportion formula, find proportion with 445/500 and input "=2.576*(SQRT(((0.89*(1-0.89))/500)))" - then subtract proportion (445/500) answer by the answer with the long formula

For a sample with df = 5, what is the t-score constant to calculate a confidence level of 95%? - 2.015 - 1.943 - 1.476 - 2.571

2.571

The t score constant used in calculating the 95% confidence interval with df=5: - 1.943 - 2.571 - 2.015 - 2.977

2.571 (Use Table B.2 - Find df of 5 and find 0.05 (95% confidence interval)

The constant used in calculating the 99% confidence interval in the proportion formula is: - 1.96 - 2.576 - 3.54 - 1.645

2.576

The constant used in calculating the 99% confidence interval in the proportions formula is: - 1.96 - 2.576 - 3.54 - 1.645

2.576 (use powerpoint z-table)

The constant used in calculating the 99% confidence interval for a sample size of 15 is: - 2.625 - 2.977 - 2.576 - 2.947

2.977 (do n-1 - so, df = 14 and find 0.01 (99% confidence interval on t-table)

When calculating the 99% confidence interval of the mean for a sample of 15 patients, what constant is used in the formula? - 2.977 - 2.603 - 2.625 - 2.947

2.977 (n-1 for df (14) and 0.01)

Which of the following is(are) true about confounding variables (choose one or more)? - A confounding variable creates an association that is misleading. - A confounding variable is associated with the outcome. - No answer text provided. - A confounding variable is associated with the exposure.

A confounding variable creates an association that is misleading, A confounding variable is associated with the outcome, A confounding variable is associated with the exposure

Is the temperature of the room during a study an extraneous or confounding variable? - Extraneous - Confounding - Neither

Extraneous (influences the outcome of an experiment and confounding variables are associated with both exposure and outcome, making the relationship look different than it really is)

How does the confidence interval relate to the significance level? - Confidence intervals are a corollary of significance levels. For example, if alpha=.05, then you can calculate the 95% CI - They are not related - They are derived from the same formula - They are inversely proportional

Confidence intervals are a corollary of significance levels. For example, if alpha=.05, then you can calculate the 95% CI (The confidence interval is the best estimate of the range of a population value. It tells you how confident you are that the population mean falls between two scores)

What CI formula would you use for a sample size of 100 subjects? - Interval/Ratio formula using the Z score - Proportions formula using the T score - Interval/Ratio formula using the T score - Proportions formula using the Z score

Interval/Ratio formula using the Z score (The interval/ratio formula using the Z score is used for sample sizes greater than 30. The interval/ratio formula using the T score is used for samples less than 30. The proportion formula is used for samples with proportions.)

As you increase your confidence level, what happens to the width of the confidence interval? - It gets narrower. - It gets wider. - It stays the same. - It gets higher.

It gets wider.

A research journal just did a 2-year study on the effects of yoga, exercise, and diet on weight loss for female adults. They only submit the significant results of the effects of exercise on weight loss. What type of bias might be a problem? - Measurement - Publication - Recall - Selection

Publication

Researchers want to determine how many times per week people walk their dogs. They select a representative sample of 250 dog owners and ask them about their dog walking habits over the last year. What type of bias might be a problem? - Selection - Measurement - Recall - Desirability

Recall

Researchers want to determine how many times per week students engage in mindfulness activities. They select a representative sample of 300 full-time students and ask them about their engagement in mindfulness activities over the past year. What type of bias might be a problem? - Selection - Recall - Measurement - Desirability

Recall (Any time research participants are asked to recall something over the past year or even over the past months the results are subject to recall bias as our memories are especially flawed and inaccurate.)

A health-focused radio show wants to determine what percentage of people in the Phoenix area are taking cholesterol medication. They ask listeners to call in and report whether or not they are taking cholesterol medication. What type of bias might be a problem? - Recall - Desirability - Measurement - Selection

Selection

What is power NOT affected by? - Sample size - Effect size - beta (β) - Standard deviation

Standard deviation (Power is affected by effect size, sample size, level of significance, and power (chosen or implied β).

What does a confidence interval tell you? - The average values of the population data - The magnitude and power of a range of population values - The variability between a range of population values - The best estimate of the range of a population value

The best estimate of the range of a population value (it tells you how confident you are that the population mean falls between two scores)

What happens to the confidence interval if we increase our sample size? - The confidence interval increases - The standard deviation increases - The confidence interval is not affected by a change in sample size - The confidence interval decreases

The confidence interval decreases (The sample size, n, in each of the confidence interval formulas is in the denominator of the equation, which means the sample size is inversely proportional to the confidence interval value.)

Why do we need confidence intervals? (choose one or more) - To express statistical uncertainty - To tell us the chance (95%) of a particular outcome - To accurately state a range of a population parameter - To give insight about the magnitude of the effect

To express statistical uncertainty, To accurately state a range of a population parameter, To give insight about the magnitude of the effect

Which of the following is considered a confounding variable for a study looking at the effects of working as a coal miner and developing cancer? - The research participant's emotions and mood - Temperature of the environment the study is conducted in - The participant is a smoker - The researcher's interaction with the participants

The participant is a smoker

Which of the following occurs when you reject the null hypothesis when it is really true? - Power - Type I error - Type II error - Sampling error

Type 1 Error

Which of the following occurs when you reject the null hypothesis when it is really true? - Type 1 error - Power - Type II error - Correct decision

Type 1 error

A _______occurs when the null hypothesis is not rejected when it is false - Type II - Type I - Type III

Type II

What affects the width of a confidence interval? (choose one or more) - Median of the sample - Variation within the population. - Our desired confidence level. - Sample size.

Variation within the population, Our desired confidence level, Sample size

Researchers find that the 90% confidence interval for men's systolic blood pressure is (126.8, 129.9). How would you interpret this? - We are 10% confident that the mean for men's systolic blood pressure is between 126.8 and 129.9 - 90% of all men's systolic blood pressure values fall between 126.8 and 129.9 - We are 90% confident that the true mean for men's systolic blood pressure is between 126.8 and 129.9. - 10% of all men's systolic blood pressure values fall between 126.8 and 129.9

We are 90% confident that the true mean for men's systolic blood pressure is between 126.8 and 129.9.

How do you interpret the confidence interval for a final exam score at a significance level of 5% that is written (71.65, 77.26)? - 95% of the final exams scores are definitely between 71.65% and 77.26% - We are 5% confident that the true mean final exam score is between 71.65% and 77.26% - 5% of the final exam scores fall between 71.65% and 77.26% - We are 95% confident that the true mean final exam score is between 71.65% and 77.26%

We are 95% confident that the true mean final exam score is between 71.65% and 77.26%

Researchers find that the 95% confidence interval for women's systolic blood pressure is (126.67, 127.93). How do you interpret this finding? - There is a 95% chance that the true mean for women's systolic blood pressure is between 126.67 and 127.93. - We are 95% confident that the true mean for women's systolic blood pressure is between 126.67 and 127.93. - 95% of the data values for women's systolic blood pressure are between 126.67 and 127.93. - All of the above.

We are 95% confident that the true mean for women's systolic blood pressure is between 126.67 and 127.93.

How do you interpret the confidence interval for women's height (in inches) at significance level of 1% that is written (62.2, 66.8)? - We are 1% confident that the true mean for women's height is between 62.2 and 66.8 inches. - The average height of women falls between 62.2 and 66.8 inches. - 99% of all women's heights fall between 62.2 and 66.8 inches. - We are 99% confident that the true mean for women's height is between 62.2 and 66.8 inches.

We are 99% confident that the true mean for women's height is between 62.2 and 66.8 inches. (The correct format for stating CI's is: We are __% confident that the true mean for the variable of interest is between ___ and ___)

When would you use the confidence interval formula for a proportion? (choose one or more) - Your sample size is under 30 - To determine if the groups are significantly different - You have summary information as a percentage or survey sample data - You do not know the population standard deviation

You have summary information as a percentage or survey sample data

Sally wants to evaluate the level of attachment between mother and child pairs. She sets up a room with toys and books and observes the interactions between each mother and child pair. The air conditioner in the room is not working properly and the observation room is extremely hot. The temperature of the room is an example of ___________________. - extraneous variable - bias - confounding - sampling error

an extraneous variable

The probability of failing to reject a null hypothesis when it is false is represented by ______________. - beta (β) - alpha (α) - p-value - test statistic

beta (β)

The probability of failing to reject a null hypothesis when it is false is represented by ______________. - power - p-value - beta (β) - alpha (α)

beta (β) - The power of a hypothesis test is the probability of rejecting the null hypothesis if the null is false. Alpha (AKA significance & Type I error) is the degree of risk a researcher is willing to take that they will reject the null when it is true. Beta (Type II error) is the risk of failing to reject the null when it is false.

________ affects the power of a study - standard deviation - population mean - effect size - standard error

effect size (power is affected by effect size, sample size ,level of significance, and power)

When calculating confidence intervals in this class the product of a constant times a margin of error is added and subtracted to what value to obtain the CI range? - alpha - mean - standard deviation - median

mean

________ = 1-β - alpha - power - significance

power (The power of a hypothesis test is the probability of rejecting the null hypothesis if the null is false and finds a difference if it actually exists. It is calculated by 1-β.)

_____is the ability of the test to discover a difference if one actually exists. - error - hypothesis - power

power (the power of a hypothesis test is the probability of rejecting the null hypothesis if the null is false and finds a difference if it actually exists)

A sports radio show wants to determine what percentage of people who exercise regularly. They ask listeners to call in and report whether they exercise regularly or not. What type of bias might be a problem? - recall - desirability - measurement - selection

selection

A type II error is made when - the alternative hypothesis is not rejected when it is true - the null hypothesis is not rejected when it is false - the alternative hypothesis is not rejected when it is false - the null hypothesis is rejected when it is true

the null hypothesis is not rejected when it is false