For 50 randomly selected speed dates, attractiveness ratings by males of their female date partners (x) are recorded along with the attractiveness ratings by females of their male date partners (y): the ratings range from 1 to 10. The 50 paired ratings yield x=6.3. y=0.0, r= -0.230, P-value = 0.100, and y = 7.82 - 0.287x. Find the best predicted value of y (attractiveness rating by female of male) for a date in which the attractiveness rating by the male of the female is x= 7. Use a 0.01 significance level. The best predicted value of y when x=7 is (Round to one decimal place as needed.)

For 50 randomly selected speed dates, attractiveness ratings by males of their female date partners (x) are recorded along with the attractiveness ratings by females of their male date partners (y): the ratings range from 1 to 10. The 50 paired ratings yield x=6.3. y=0.0, r= -0.230, P-value = 0.100, and y = 7.82 - 0.287x. Find the best predicted value of y (attractiveness rating by female of male) for a date in which the attractiveness rating by the male of the female is x= 7. Use a 0.01 significance level. The best predicted value of y when x=7 is (Round to one decimal place as needed.)

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

Thomas wants to compare the mean concentration of carbon monoxide (CO) on residential versus commercial streets, since these differ in terms of car traffic. In each of three neighborhoods of Montréal (named A, B, and C below), he randomly chooses four locations for each type of street, for a total of 24 observations (2 street types x 3 neighborhoods x 4 locations). At each location, he measures CO concentration in the air over a period of 10 hours (8:00 AM-6:00 PM), and obtains the following data (in ppm/h). Question: Test whether or not the difference between residential and commercial streets in mean atmospheric CO concentration is the same among the three neighborhoods, and whether or not CO concentration in the air is the same, on average, for the two types of streets. Note that Neighborhood is considered a random block factor in the ANOVA. Use significant level= 0.05.
Suppose the mean of Z is 2. What is the mean of Y if a = 1.22 and Y=aZ? (Use two decimal places, ex: 12.34)
Suppose u, and u, are true mean stopping distances at 50 mph for cars of a certain type equipped with two different types of braking systems. The data follows: m = 5, x = 115.1, s, = 5.05, n = 5, y = 129.2, and s, = 5.36. Calculate a 95% CI for the difference between true average stopping distances for cars equipped with system 1 and cars equipped with system 2. (Round your answers to two decimal places.) n USE SALT Does the interval suggest that precise information about the value of this difference is available? O Because the interval is so narrow, it appears that precise information is available. o Because the interval is so wide, it appears that precise information is not available. o Because the interval is so narrow, it appears that precise information is not available. Because the interval is so wide, it appears that precise information is available. You may need to use the appropriate table in the Appendix of Tables to answer this question.
The weights (in pounds) of 6 vehicles and the variability of their braking distances (in feet) when stopping on a dry surface are shown in the table. Can you conclude that there is a significant linear correlation between vehicle weight and variability in braking distance on a dry surface? Use a = 0.05. Weight, x Variability in braking distance, y 5980 5370 6500 5100 5820 4800 1.72 1.97 1.87 1.63 1.64 1.50 Click here to view a table of critical values for Student's t-distribution. Setup the hypothesis for the test. Ho: Ha: P Identify the critical value(s). Select the correct choice below and fill in any answer boxes within your choice. (Round to three decimal places as needed.) O A. The critical value is. B. The critical values are - to and to %3D Calculate the test statistic. t= (Round to three decimal places as needed.) What is your conclusion? There enough evidence at the 5% level of significance to conclude that there a significant linear correlation between vehicle weight and…
The line of best fit through a set of data is y = – 27.749 + 1.474x According to this equation, what is the predicted value of the dependent variable when the independent variable has value 30? y = Round to 1 decimal place.
Choose the value of the Pearson's Correlation Coefficient (r) that best describes the two plots. : 0.504, II: -0.232. 2) I: -0.904, II: 0.232. 3) I: 0.904, II: -0.232. 4) I: -0.232, II: 1.304. 5) I: 0.904, II: -0.632.
A PSYC 2330 student wants to determine if caffeine effects cognitive function. A group of fifteen year olds’ math abilities are measured before to establish a baseline, after they consumed one cup of coffee, and again when they consume a placebo. Analysis: ? Ho:?
Suppose u1 and uz are true mean stopping distances at 50 mph for cars of a certain type equipped with two different types of braking systems. The data follows: m = 6, x = 115.6, s1 = 5.03, n = 6, y = 129.9, and s2 = 5.38. Calculate a 95% CI for the difference between true average stopping distances for cars equipped with system 1 and cars equipped with system 2. (Round your answers to two decimal places.) In USE SALT Does the interval suggest that precise information about the value of this difference is available? Because the interval is so narrow, it appears that precise information is available. Because the interval is so narrow, it appears that precise information is not available. o Because the interval is so wide, it appears that precise information is not available. o Because the interval is so wide, it appears that precise information is available.
If you have 10 variables when computing correlation coefficients how many unique coefficients will you have overall?
A random sample of college students was surveyed about how they spend their time each week. The scatterplot below displays the relationship between the number of hours each student typically works per week at a part- or full-time job and the number of hours of television each student typically watches per week. The correlation between these variables is r = –0.63, and the equation we would use to predict hours spent watching TV based on hours spent working is as follows: Predicted hours spent watching TV = 17.21 – 0.23(hours spent working) Since we are using hours spent working to help us predict hours spent watching TV, we’d call hours spent working a(n) __________________ variable and hours spent watching TV a(n) __________________ variable. The correlation coefficient, along with what we see in the scatterplot, tells us that the relationship between the variables has a direction that is _________________ and a strength that is ______________________. According to the…
The y for the association between education and health is -0.386. Does y for the relationship between frequency of prayer and health (-.055) represent a stronger or weaker ordinal association then the y of -0.386 for the relationship between education and health? Options: A. stronger relationship than y of -0.386 B. Weaker relationship than y of 0.386 C. cant tell from the information provided
e. Compute the covariance and correlation coefficient r between the right tire pressure. f. How do you know the relationship between pressure in the left and right tires is positive. g. What value would a correlation coefficient (r) be close to if there was no (linear) relationship between the 2 tire pressures?