Morning Testing М- 15 М - 19 Afternoon Testing М-13 Older Adults Younger Adults M = 20 9. Does there appear to be a main effect of time of day? 10. Does there appear to be a main effect of age? 1 1. Does there appear to be an interaction between age and time of day? (Hint: Draw a

Morning Testing М- 15 М - 19 Afternoon Testing М-13 Older Adults Younger Adults M = 20 9. Does there appear to be a main effect of time of day? 10. Does there appear to be a main effect of age? 1 1. Does there appear to be an interaction between age and time of day? (Hint: Draw a

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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ch 11 end. 7: In a bumper test, three test vehicles of each of three types of autos were crashed into a barrier at 5 mph, and the resulting damage was estimated. Crashes were from three angles: head-on, slanted, and rear-end. The results are shown below. Research questions: Is the mean repair cost affected by crash type and/or vehicle type? Are the observed effects (if any) large enough to be of practical importance (as opposed to statistical significance)?
Aspirin III: Decision and Conclusion Regarding the experiment in the data frame Aspirin from the abd package, the researchers wanted to know whether or not taking aspirin affects one's risk of developing cancer. Recall that they defined their parameters as follows: p1 = the proportion of ALL individuals who would develop cancer, if all of them were to take aspirin like the subjects in the Aspirin group did. p2 = the proportion of ALL individuals who would develop cancer, if all of them were to take a placebo, like the subjects in the placebo group did. They ran the code for a two-sided significance test and got the following results: ## ## ## Inferential Procedures for the Difference of Two Proportions p1-p2:## cancer grouped by treatment ## ## ## Descriptive Results:## ## yes n estimated.prop## Aspirin 1438 19934 0.07214## Placebo 1427 19942 0.07156## ## ## Inferential Results:## ## Estimate of p1-p2: 0.0005805 ## SE(p1.hat - p2.hat): 0.002586 ## ##…
8. Trace metals in drinking water affect the flavor of the water, and un-usually high concentration can pose a health hazard. Table 1 shows trace-metal concentrations (zinc, in mg/L) for both surface water and bottom water at six different river locations. Our aim is to see if surface water concentration (x) is predictive of bottom water concentration (y). a. State the independent and dependent variable? b. State the Ho y HA c. Draw a scatter diagram to show a possible association between the concentrations and check to see if a linear model is justified. d. Calculate the correlation coefficient and provide your interpretation. e. Find the regression equation and pro your interpretation. Table 1 1123456 Location Bottom 0.430 0.266 0.567 0.531 0.707 0.716 Surface 0.415 0.238 0.390 0.410 0.605 0.609 I
2.2 In the following descriptions of a study, confounding is present. Describe the explanatory and confounding variable in the study and how the confounding may invalidate the conclusions of the study. Furthermore, suggest how you would change the study to eliminate the effect of the confounding variable. A hospital introduces a new screening procedure to identify patients suffering from a stroke so that a new blood clot medication can be given to the patient during the crucial period of 12 hours after stroke begins. The procedure appears to be very successful because in the first year of its implementation there is a higher rate of total recovery by the patients in comparison to the rate in the previous year for patients admitted to the hospital. A high school mathematics teacher is convinced that a new software program will improve math scores for students taking the SAT. As a method of evaluating her theory, she offers the students an opportunity to use the software on the…
15) Fine the sum of products (SP) and sum of squares (SS) for the variables of interest mentioned in the study above. Then find the correlation between the two variables of interest. (Round all answers to 2 decimal points) a) SP = b) SSbullying = c) SSprejudice = d) r =
Only question from part d to g
Section 6.3: Hypothesis Test of Differences in Proportions Example 4. Autism and Maternal Antidepressant Use A recent study41 compared 298 children with Autism Spectrum Disorder to 1507 randomly selected control children without the disorder. Of the children with autism, 20 of the mothers had used antidepressant drugs during the year before pregnancy or the first trimester of pregnancy. Of the control children, 50 of the mothers had used the drugs. (a) Is there a significant association between prenatal exposure to antidepressant medicine and the risk of autism? Test whether the results are significant at the 5% level. (b) Can we conclude that prenatal exposure to antidepressant medicine increases the risk of autism in the child? Why or why not?
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Q2. A fast-food chain decided to carry out an experiment to assess the influence of advertising expenditure on sales. Different relative changes in advertising expenditure, compared to the previous year, were made in eight regions of the country, and resulting changes in sales levels were observed the accompanying table shows the results. Increase in advertising expenditure (%) 0 5 15 20 25 30 35 40 Increase in sales (%) 5 10 18 25 35 50 60 65 Determine the value of ∑X, ∑X2, ∑Y, ∑Y2, ∑XY. Where X represent independent variable and Y for dependent variable. [2] Determine and interpret the coefficient of correlation between the two variables. [1] Determine the value of regressions coefficients and write down the simple linear regression
2. A researcher had rats engage in a lever-press task for either a small, medium, or larger reward. The number of lever presses was the dependent variable. The data were as follows: Reward Size Small Medium Large 1 4 6 4 3 5 1 4 4 2 5 T = 13 SS = 2.75 T= 6 T= 20 SS = 9 SS = 2 EX2 = 165 a. Do the data indicate that reward size had a significant impact on lever-pressing? Use the hypothesis testing steps & p = .05. Compute any necessary post-hoc tests. b. Compute eta-squared to measure the effect size.
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I need help with this question 1. Are the main effects significant? Explain