Q3) A set of data is shown to have a linear relationship if transformed into the function log(y)=2+5x. Transform that relationship back into a direct relationship between x and y. What is the value of y when x =0.1 ? I

A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-0.649 b=20.136 r2=0.488601 r=-0.699 Use this to predict the number of situps a person who watches 2.5 hours of TV can do (to one decimal place)

A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-0.649 b=20.136 r2=0.488601 r=-0.699 Use this to predict the number of situps a person who watches 2.5 hours of TV can do (to one decimal place)

Based on the scatterplot and residual plot, what type of model would be appropriate for summarizing the relationship between days and number of views? A popular television show recently released a video preview for the upcoming season on its website. As fans of the show discover the video, the number of views of the preview video has grown each day during the last 2 weeks. The number of days since the release of the video and the natural log of the number of video views is shown in the scatterplot. O An exponential model is appropriate because the residual plot does not show a clear pattern. O A linear model is appropriate because the scatterplot shows a strong, positive linear relationship. In(Views) vs. Days O A power model is appropriate because the scatterplot of days and natural log of views is strong and linear. 10 9.5 An exponential model is appropriate because the relationship between days and the natural log of views is linear, and the residual plot does not show a clear…

Please explain as detail as possible, thanks

A regression was run to determine if there is a relationship between hours of study per week (z) and the final exam scores (y). The results of the regression were: y=ax+b a=6.578 b-20.35 r-0.3721 r=0.61 Use this to predict the final exam score of a student who studies 7 hours per week, and please round your answer to a whole number.

A regression was run to determine if there is a relationship between hours of TV watched per day (x) and the number of sit-ups a person can do (y). The results were: y = a+bx b = -0.89 a = 23.49 r² = 0.6519 r = -0.8074 a. If a person watches 7 hours of television a day, predict how many sit-ups he can do. b. If a person can do 4 sit ups, predict how many hours of television a day they watch. hours

A regression analysis was performed to determine if there is a relationship between hours ofTV watched per day r) and number of sit ups a person can do (y). The results of the regression were: у-ах+b a=-0.827 b=35.329 r2=0.540225 r=-0.735 Use this to predict the number of sit ups a person who watches 13.5 hours of TV can do, and please round your answer to a whole number.

A chemistry experiment is performed measuring the solubility of potassium chloride (KCl) in water at different temperatures. The goal was to determine if there is a linear relationship between the temperature of the water and how much KCl can dissolve, measured as grams per 100 milliliter (g/100mL). After the experiments were performed, the following data was collected with temperature being the independent x-variable and solubility being the dependent y-variable: Temperature (°C) x Solubility (g/100mL) y 10 31 20 33 30 37 40 41 50 42 Based on the data given for temperature and solubility of KCl and without doing any math yet, which of the following do you predict would best describe the relationship between these variables?     A positive linear relationship (r close to 1)     A positive linear relationship (r close to -1)     A negative linear relationship (r close to 1)     A negative linear relationship (r close to -1)…

While collecting data on shoe sizes (y) compared to heights in inches (x) of male students in the class a student found that the shoe sizes ranged from size 7 to size 11 and the heights of the students ranged from 60 to 72 inches. The student ran a linear regression to get the function = 1 -x- 3 13 where y is the shoe size and is the height of the person in inches. What would be the shoe size for a student who was 73 inches tall? Shoe sizes only show up in incriments of 0.5 (ie. 7, 7.5, 8, 8.5, 9, 9.5, ....) so round to the nearest 1/2 shoe size. Show all your work.