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A researcher wants to know if there is a difference between the mean amount of sleep that people get for various types of employment status. The table below shows data that was collected from a survey. Full Time Worker Part Time Worker Unemployed 7 118700 5 1 F 7 6 Ho: μι = με – με H₁: At least two of the means differ from each other. JANOVA 46860006 7 8 9 7 8 10 Assume that all distributions are normal, the three population standard deviations are all the same, and the data was collected independently and randomly. Use a level of significance of a = 0.1. 10 10 10 10

A researcher wants to know if there is a difference between the mean amount of sleep that people get for various types of employment status. The table below shows data that was collected from a survey. Full Time Worker Part Time Worker Unemployed 7 118700 5 1 F 7 6 Ho: μι = με – με H₁: At least two of the means differ from each other. JANOVA 46860006 7 8 9 7 8 10 Assume that all distributions are normal, the three population standard deviations are all the same, and the data was collected independently and randomly. Use a level of significance of a = 0.1. 10 10 10 10

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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A researcher wants to know if there is a difference between the mean amount of sleep that people get for various types of employment status. The table below shows data that was collected from a survey. Full Time Worker Part Time Worker Unemployed 8 7 7 5 8 7 7 7 6 Ho : μ41= µ42=143 H₁: At least two of the means differ from each other. 1. For this study, we should use ANOVA 9 7 8 2. The test-statistic for this data = 2 3. The p-value for this sample = 1 4. The p-value is less than (or equal to) alpha ✓ ✓ o 5. Base on this, we should reject the null hypothesis 6 9 8 9 7 7 8 10 Assume that all distributions are normal, the three population standard deviations are all the same, and the data was collected independently and randomly. Use a level of significance of a = 0.1. 10 10 10 10 x (Please show your answer to 3 decimal places.) x (Please show your answer to 4 decimal places.) hypothesis 6. As such, the final conclusion is that... O There is insufficient evidence to support the claim that employment status is a factor in the amount of sleep people get. There is sufficient evidence to support the claim that employment status is a factor in the amount of sleep people get.
Transcribed Image Text:A researcher wants to know if there is a difference between the mean amount of sleep that people get for various types of employment status. The table below shows data that was collected from a survey. Full Time Worker Part Time Worker Unemployed 8 7 7 5 8 7 7 7 6 Ho : μ41= µ42=143 H₁: At least two of the means differ from each other. 1. For this study, we should use ANOVA 9 7 8 2. The test-statistic for this data = 2 3. The p-value for this sample = 1 4. The p-value is less than (or equal to) alpha ✓ ✓ o 5. Base on this, we should reject the null hypothesis 6 9 8 9 7 7 8 10 Assume that all distributions are normal, the three population standard deviations are all the same, and the data was collected independently and randomly. Use a level of significance of a = 0.1. 10 10 10 10 x (Please show your answer to 3 decimal places.) x (Please show your answer to 4 decimal places.) hypothesis 6. As such, the final conclusion is that... O There is insufficient evidence to support the claim that employment status is a factor in the amount of sleep people get. There is sufficient evidence to support the claim that employment status is a factor in the amount of sleep people get.
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Thank you so much,  I also need help with this one parts. thank you

A, B, D F G

A biologist looked at the relationship between number of seeds a plant produces and the percent of those seeds that sprout. The results of the survey are shown below. Seeds Produced 68 56 61 Sprout Percent 60.6 69.2 = 0 48 64.7 64.6 #0 a. Find the correlation coefficient: b. The null and alternative hypotheses for correlation are: H₂: ? H₁: 2 The p-value is: 63 64.1 40 Round to 2 decimal places. 63 62 65.1 68.4 84 (Round to four decimal places) c. Use a level of significance of a = 0.05 to state the conclusion of the hypothesis test in the context of the study. O There is statistically significant evidence to conclude that there is a correlation between the number of seeds that a plant produces and the percent of the seeds that sprout. Thus, the regression line is useful. O There is statistically insignificant evidence to conclude that a plant that produces more seeds will have seeds with a lower sprout rate than a plant that produces fewer seeds. O There is statistically significant evidence to conclude that a plant that produces more seeds will have seeds with a lower sprout rate than a plant that produces fewer seeds. O There is statistically insignificant evidence to conclude that there is a correlation between the number of seeds that a plant produces and the percent of the seeds that sprout. Thus, the use of the regression line is not appropriate. (Round to two decimal places) f. The equation of the linear regression line is: d. ²= e. Interpret ²: O There is a 65% chance that the regression line will be a good predictor for the percent of seeds that sprout based on the number of seeds produced. O 65% of all plants produce seeds whose chance of sprouting is the average chance of sprouting. O Given any group of plants that all produce the same number of seeds, 65% of all of these plants will produce seeds with the same chance of sprouting. O There is a large variation in the percent of seeds that sprout, but if you only look at plants that produce a fixed number of seeds, this variation on average is reduced by 65%. (Please show your answers to two decimal places) g. Use the model to predict the percent of seeds that sprout if the plant produces 55 seeds. Percent sprouting = (Please round your answer to the nearest whole number.) h. Interpret the slope of the regression line in the context of the question: O For every additional seed that a plant produces, the chance for each of the seeds to sprout tends to decrease by 0.62 percent. i. Interpret the y-intercept in the context of the question: O The slope has no practical meaning since it makes no sense to look at the percent of the seeds that sprout since you cannot have a negative number. O As x goes up, y goes down. O The average sprouting percent is predicted to be 103.39. O If plant produces no seeds, then that plant's sprout rate will be 103.39. O The y-intercept has no practical meaning for this study. O The best prediction for a plant that has 0 seeds is 103.39 percent.
Transcribed Image Text:A biologist looked at the relationship between number of seeds a plant produces and the percent of those seeds that sprout. The results of the survey are shown below. Seeds Produced 68 56 61 Sprout Percent 60.6 69.2 = 0 48 64.7 64.6 #0 a. Find the correlation coefficient: b. The null and alternative hypotheses for correlation are: H₂: ? H₁: 2 The p-value is: 63 64.1 40 Round to 2 decimal places. 63 62 65.1 68.4 84 (Round to four decimal places) c. Use a level of significance of a = 0.05 to state the conclusion of the hypothesis test in the context of the study. O There is statistically significant evidence to conclude that there is a correlation between the number of seeds that a plant produces and the percent of the seeds that sprout. Thus, the regression line is useful. O There is statistically insignificant evidence to conclude that a plant that produces more seeds will have seeds with a lower sprout rate than a plant that produces fewer seeds. O There is statistically significant evidence to conclude that a plant that produces more seeds will have seeds with a lower sprout rate than a plant that produces fewer seeds. O There is statistically insignificant evidence to conclude that there is a correlation between the number of seeds that a plant produces and the percent of the seeds that sprout. Thus, the use of the regression line is not appropriate. (Round to two decimal places) f. The equation of the linear regression line is: d. ²= e. Interpret ²: O There is a 65% chance that the regression line will be a good predictor for the percent of seeds that sprout based on the number of seeds produced. O 65% of all plants produce seeds whose chance of sprouting is the average chance of sprouting. O Given any group of plants that all produce the same number of seeds, 65% of all of these plants will produce seeds with the same chance of sprouting. O There is a large variation in the percent of seeds that sprout, but if you only look at plants that produce a fixed number of seeds, this variation on average is reduced by 65%. (Please show your answers to two decimal places) g. Use the model to predict the percent of seeds that sprout if the plant produces 55 seeds. Percent sprouting = (Please round your answer to the nearest whole number.) h. Interpret the slope of the regression line in the context of the question: O For every additional seed that a plant produces, the chance for each of the seeds to sprout tends to decrease by 0.62 percent. i. Interpret the y-intercept in the context of the question: O The slope has no practical meaning since it makes no sense to look at the percent of the seeds that sprout since you cannot have a negative number. O As x goes up, y goes down. O The average sprouting percent is predicted to be 103.39. O If plant produces no seeds, then that plant's sprout rate will be 103.39. O The y-intercept has no practical meaning for this study. O The best prediction for a plant that has 0 seeds is 103.39 percent.
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