Imagine we conducted a study that found that pedestrians were more likely to give money to astreet beggar if the beggar had a cute and hungry-looking dog with them, and this effect wasidentical for both male and female pedestrians. If we calculated the difference between men andwomen in the no dog condition and plotted this value against the difference between men andwomen in the dog condition, which of the following values is most likely to represent the gradientof our graph?A22.7В33.8C1D

Given: We conducted a study that found that pedestrians were more likely to give money to a street…

Answered: Imagine we conducted a study that found…

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 researcher wanted to predict the sodium content (in milligrams) of beef hot dogs by looking at the calorie content. His findings from a sample of 10 beef hot dogs are summarized below. The regression equation for his data is ŷ= -299.48 + 4.35 x Calories 186 181 176 149 184 190 158 139 175 148 Sodium 495 477 425 322 482 587 370 322 479 375 Interpret the slope in terms of this problem. If appropriate, find the sodium content if the calorie content is 170. If not, why? If appropriate, find the sodium content if the calorie content is 136. If not, why?
In industry, the relationship between wages and the quit ratio of employees is defined to be the percentage of employees that quit within 1 year of employment. The quit ratio of a large restaurant chain that paid its employees the minimum hourly wage ($7.25 per hour) was .2 or 20 employees per 100. When the company raised the hourly wage to $8, the quit ratio dropped to .18, or 18 employees per 100. (a) Assuming a linear relationship between the quit ratio Q(x) and the hourly wage x, find an expression for Q(x). (b) What should the hourly wage be for the quit ratio to drop to 10 employees per 100?
Suppose trips/wk =3.1 -0.15(dist) is a linear model that predicts the number of supermarket trips a family makes per week when they live a certain distance (in miles) from a supermarket. It was established by sampling people who live within 10 miles of a supermarket. Which of the following is the correct interpretation of the slope? O a. For each additional trip that the family makes, they live 0.15 miles away from the store O b. For each additional mile away from the store the family lives, they make 0.15 more visits per week O. For each additional mile away from the store the family lives, they make 0.15 fewer visits per week O d. For each additional trip they make to the store, they live an additional 3.1 miles away. O e. For each additional mile away they live, they make 3.1 more trips to the stor.
The following linear regression model can be used to predict ticket sales at a popular water park. Ticket sales per hour = - 631.25 + 11.25(current temperature in °F)23) Choose the statement that best states the meaning of the slope in this context. A) The slope tells us that a one degree increase in temperature is associated with an average increase in ticket sales of 11.25 tickets. B) The slope tells us that high temperatures are causing more people to buy tickets to the water park. C) The slope tells us that if ticket sales are decreasing there must have been a drop in temperature. D) None of these
Please help
Help with question 2 and 3 please. Help with question 2 and 3 please.
Which of the slopes matches best with the slope of the data in the scatter plot? would it be m = 3/8?, m = 8/3?, m = - 3/8? or would it be m = - 8/3???
Below is the actual data on the speed a person walks or runs in miles/hour and the calories the person burns per lap. Find the linear equation of best fit for this data. Compare the model to the data. Does the model seem to fit the data? Explain. What is the significance of the y-intercept? What is the slope and what does it mean? What is the x-intercept and what does it mean? What is the correlation coefficient and what does it mean? Speed (mph) Calories/lap 1 42 2 31 3 27 4 41 5 40 6 40 7 39 8 38 r answers to the nearest hundredth. The y-intercept means that if a person runs at ----------mph they will burn__________ per lap. The slope means that for each mph you increase your speed, you will burn an additional------------calories pay lap
A researcher wishes to examine the relationship between years of schooling completed and the number of pregnancies in young women. Her research discovers a linear relationship, and the model is: ý = 3 – 4x where x is the number of years of schooling completed and y is the number of pregnancies. The slope of this line can be interpreted in the following way: O When amount of schooling increases by one year, the number of pregnancies tends to decrease by 4. O When amount of schooling increases by one year, the number of pregnancies tends to decrease by 3. O When amount of schooling increases by one year, the number of pregnancies tends to increase by 3. O When amount of schooling increases by one year, the number of pregnancies tends to increase by 4.
Range of ankle motion is a contributing factor to falls among the elderly. Suppose a team of researchers is studying how compression hosiery, typical shoes, and medical shoes affect range of ankle motion. In particular, note the variables Barefoot and Footwear2. Barefoot represents a subject's range of ankle motion (in degrees) while barefoot, and Footwear2 represents their range of ankle motion (in degrees) while wearing medical shoes. Use this data and your preferred software to calculate the equation of the least-squares linear regression line to predict a subject's range of ankle motion while wearing medical shoes, ?̂ , based on their range of ankle motion while barefoot, ? . Round your coefficients to two decimal places of precision. ?̂ = A physical therapist determines that her patient Jan has a range of ankle motion of 7.26°7.26° while barefoot. Predict Jan's range of ankle motion while wearing medical shoes, ?̂ . Round your answer to two decimal places. ?̂ = Suppose Jan's…
The number (in millions) of employees working in educational services in a particular country was 13.8 in 2005 and 18.2 in 2014. Let x = 5 correspond to the year 200 and estimate the number of employees in 2010. Assume that the data can be modeled by a straight line and that the trend continues indefinitely. Use two data points find such a line and then estimate the requested quantity. ... Let y represent the number of employees. The linear equation that best models the number of employees (in millions) is (Simplify your answer. Use integers or decimals for any numbers in the equation. Round to the nearest hundredth as needed.) In 2010, the number (in millions) of employees working in education services would be (Type an integer or a decimal rounded to the nearest hundredth as needed.)
If the regression line showing the effect of education on income has a slope of 1000. a) the variables are not related b) the Y intercept would be 1.00 c) every change in education increases income d) every year of education increases income by 1000

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