4. All but one of these statements contain a mistake. Which could be true?A. The correlation between a car's length and its fuel efficiency is 0.71 miles per gallon.B. There is a correlation of 0.63 between gender and political party.C. There is a high correlation (1.09) between height of a corn stalk and its age in weeks.The correlation between the amount of fertilizer used and the yield of beans 0.42.E. The correlation between a football player's weight and the position he plays is 0.54.5. A company's sales increase by the same amount each year. This growth is...A. quadraticB. exponentialC. linearD. logarithmicE. power

Dear students as per guidelines we solve only first question when questions are different. Solution…

Answered: 4. All but one of these statements…

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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A statistics professor finds that he can predict a student's grade on the final exam based on the number of classes the student attended over the course of the semester. What is the casual relationship between these two variables? a. Students who do well on exams are going to come to class because they enjoy the material. b. We cannot say anything definitive about the casual relationships, as all three of these explanations are possible. c. The relationship likely is the result of some third variable which accounts for both a student's attendance in class and his or her performance on the exam. d. Attendence in classes causes students to understand the material and do well on the exams.
Seventy-six Starbucks food items were analyzed for the calorie and carbohydrate content. We used linear regression to explore the relationship between the number of calories and amount of carbohydrates (in grams) Starbucks food menu items contain. The estimated regression equation with carbohydrates as the response variable and the calories as the explanatory variable is ŷ = 8.94 + 0.11x, and summary statistics of the two variables is provided below. variable min Q1 median Q3 max mean sd n missing calories 80 300 350 420 500 338.8 105.4 77 carbohydrates 16 31 45 59 80 44.9 16.6 77
4. Slow down and save Fuel efficiency for many cars is related to how fast the car is driven. To explore this relationship, some researchers calculated the mean fuel efficiency for nine different car models at 13 different speeds. Here are the results. Speed (mph) 15 20 25 30 35 40 45 50 55 60 65 70 75 Mean fuel efficiency (mpg) 24.4 27.9 30.5 31.7 31.2 31.0 31.6 32.4 32.4 31.4 29.2 26.8 24.8 (a) Calculate a quadratic model for these data using speed as the explanatory variable. (b) Sketch the scatterplot, along with the quadratic model. (c) Calculate and interpret the residual for the cars traveling 60 miles per hour.
4. What graphical display is the most suitable to show whether there is a relationship between the age of a person and the number of hours per week spent on exercising?
Joan's Nursery specializes in custom-designed landscaping for residential areas. The estimated labor cost associated with a particular landscaping proposal is based on the number of plantings of trees, shrubs, and so on to be used for the project. For cost-estimating purposes, managers use two hours of labor time for the plant- ing of a medium-sized tree. Actual times from a sample of 10 plantings during the past month follow (times in hours).2.1 2.2 1.7 1.6 2.3 3.1 1.5 2.6 2.4 2.2 With a .05 level of significance, test to see whether the mean tree-planting time differs from two hours. a. State the null and alternative hypotheses. b. Compute the sample mean. c. Compute the sample standard deviation. d. What is the p-value? e. What is your conclusion?
B. What is the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute? The best predicted temperature when a bug is chirping at 3000 chirps per minute is____°F. C. What is wrong with this predicted value? The first variable should have been the dependent variable. It is unrealistically high. The value 3000 is far outside of the range of observed values. It is only an approximation. An unrounded value would be considered accurate. Nothing is wrong with this value. It can be treated as an accurate prediction.
4.4
Cathy makes a single deposit into an account earning 2.5% compounded monthly. After five years the account contains $3057.46.how much did she deposit?
Identifying individuals with a high risk of Alzheimer's disease usually involves a long series of cognitive tests. However, researchers have developed a 7-Minute Screen, which is a quick and easy way to accomplish the same goal. The question is whether the 7-Minute Screen is as effective as the complete series of tests. To address this question, Ijuin et al. (2008) administered both tests to a group of patients and compared the results. The following data represent results similar to those obtained in the study. 7-Minute Screen Cognitive Series 3 11 8 19 10 22 8 20 4 14 7 13 4 9 5 20 14 25 Which statistical test would you select: Answer H0: Answer H1: Answer What is the coefficient that indicates the strength of the relationship? Answer =Answer What is the standard error? Answer What is the appropriate 95% CI? [ Answer , Answer ] What is the d-effect size? Answer What is the t-observed? Answer What is the actual p-value? Answer THREE decimal places…
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8. Determine if the correlation between the two given variables is likely to be positive or negative, or if they are not likely to display a linear relationship. a) The average selling price of a model of car and the cost of a loaf of bread on a given day b) The number of crimes committed in an area and the selling price of homes in that area c) The number of pets owned by a family and the cost of their vet bills
A 7. The analyst in the Dorben Company made 10 independent time studies in the hand paint- spraying section of the finishing department. The product line under study revealed a direct relation between spraying time and product surface area. The following data were collected. Study No. 1 2 3 4 5 6 8 9 10 Surface Area 170 12 150 41 130 50 70 105 95 (sq. inches) Standard Time (hours) 0.32 0.11 0.31 0.14 0.27 0.18 7 120 0.24 0.23 0.25 (7a) Compute the slope and intercept constant using regression line equations. (7b) What is the correlation coefficient? (7c) How much spray time would you allow for a new part with a surface area of 250 sq. inches? 0.22

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