Suppose a psychologist used number of hours of sleep in the night before a quiz to predict the quiz score using simple linear regression. The mean number of hours of sleep is 6.28 and the SD is 2. The standardized coefficient (beta in SPSS) is 0.38. If the number of hours of sleep increases from 6.28 to 8.28, what is the increase in predicted quiz score in standard deviation?

Suppose a psychologist used number of hours of sleep in the night before a quiz to predict the quiz score using simple linear regression. The mean number of hours of sleep is 6.28 and the SD is 2. The standardized coefficient (beta in SPSS) is 0.38. If the number of hours of sleep increases from 6.28 to 8.28, what is the increase in predicted quiz score in standard deviation?

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

5.34 Please complete both parts. Do Part (a) "by hand": the mean height of the brothers is 69 inches and the standard deviation is 2.72 inches, the mean height of the sisters is 64 inches and the standard deviation is 2.57 inches, and the correlation is 0.558. Draw the scatterplot by hand. The regression line can be approximate
Consider a regression that uses X = # of 60 pound bench press repetitions to predict Y = maximum bench press amount in pounds…..for the ith student among a sample of high school athletes. The estimated predicted sample regression is as follows Maxi= 68.91 + .6885Repsi *the ei is left off for simplicity The table below lists the actual data from which the regression above was estimated. For example, a student in the study who trained by doing 12 “60 pound reps” accomplished a maximum bench press amount of 76 pounds. Xi Yi 12 76 15 82 17 79 3 71 Predict the average maximum bench press for a student that does 17 “60 pound reps” a) a. around 68.85 pounds b) b. around 85.00 pounds c) c. around 80.61 pounds d) d. around 68.91 pounds
Suppose you are analyzing a dataset of 77 datapoints investigating the relationship between the number of theme park visitors (dependent variable) and temperature (independent variable). You decide to create a simple linear regression model, which yields a sum of squared residuals of e²=546.51. Using this information, what was the residual standard deviation (Se) found in your analysis? Note: 1- Only round your final answer. Round your final answer to two decimal places.
The denominator of the Pearson correlation coefficient measures the extent to which two factors vary together. True False
What kind of plot is useful for deciding whether it is reasonable to find a regression plane for a set of data points involving several predictor variables?
A regression model to predict Y, the state burglary rate per 100,000 people, used the following four state predictors: X1 = median age, X2 = number of bankruptcies per 1,000 population, X3 = federal expenditures per capita (a leading predictor), and X4 = high school graduation percentage. Click here for the Excel Data File (a) Using the sample size of 45 people, calculate the tcalc and p-value in the table given below. (Negative values should be indicated by a minus sign. Leave no cells blank - be certain to enter "0" wherever required. Round your t-values to 3 decimal places and p- values to 4 decimal places.) Predictor Intercept AgeMed Coefficient SE tcalc p-value 4,641.0430 798.0634 -28.8630 12.4684 Bankrupt 20.1604 12.1079 FedSpend HSGrad% -0.0181 0.0181 -30.3196 7.1136 (b-1) What is the critical value of Student's tin Appendix D for a two-tailed test at a = .01? (Round your answer to 3 decimal places.) -value =
21
Listed below are altitudes (thousands of feet) and outside air temperatures (°F) recorded during a flight. Find the (a) explained variation, (b) unexplained variation, and (c) indicated prediction interval. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. For the prediction interval, use a 95% confidence level with the altitude of 6327 ft (or 6.327 thousand feet). Altitude 8 15 22 28 31 33 Temperature 56 39 24 - 28 - 41 - 60 a. Find the explained variation. (Round to two decimal places as needed.)
A colleague of yours is completing a final report on the causes of the frequency of cyberbullying. In this report, she is asked to identify the causes that most strongly impacted the frequency of cyberbullying. She conducts an OLS regression. What statistic do you advise her to use in her discussion? Why?
The accompanying table lists overhead widths (cm) of seals measured from photographs and the weights (kg) of the seals. Find the (a) explained variation, (b) unexplained variation, and (c) prediction interval for an overhead width of 8.9 cm using a 99% confidence level. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. Click the icon to view the seal data. a. The explained variation is (Round to the nearest integer as needed.) b. The unexplained variation is. (Round to the nearest integer as needed.) c. The 99% prediction interval for an overhead width of 8.9 cm is kg
Listed below are altitudes (thousands of feet) and outside air temperatures (°F) recorded during a flight. Find the (a) explained variation, (b) unexplained variation, and (c) indicated prediction interval. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. For the prediction interval, use a 95% confidence level with the altitude of 6327 ft (or 6.327 thousand feet). Altitude Temperature a. Find the explained variation. (Round to two decimal places as needed.) 2 55 8 40 13 25 20 - 3 28 - 26 31 - 41 34 - 53
The table below lists weights (carats) and prices (dollars) of randomly selected diamonds. Find the (a) explained variation, (b) unexplained variation, and (c) indicated prediction interval. There is sufficient evidence o support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. For the prediction interval, use a 95% confidence level with a diamond that weighs 0.8 carats. Weight Price 0.3 $508 a. Find the explained variation. 0.4 $1153 0.5 $1332 Round to the nearest whole number as needed.) . Find the unexplained variation. Round to the nearest whole number as needed.) c. Find the indicated prediction interval.