1.The temperature outside and the air conditioning cost 2. The amount of screen time in a week and a shoe size 3. The amount of gas in your boat and the time spent water skiing

Two variables are found to have a strong positive linear correlation. Pick the correct statement. An increase in one variable potentially causes a decrease in the other. An increase in one variable does not cause a decrease in the other. An increase in one variable does not cause an increase in the other. An increase in one variable potentially causes an increase in the other. An increase in one variable causes a decrease in the other. An increase in one variable causes an increase in the other.

Jim and Larry run a soup stand. The data below represents the sales of soup that they had on 8 randomly selected days, along with the high temperature on that day.   a) Create a scatter diagram for this data set and comment on whether there is a positive or negative relationship between these variables.b) Calculate the correlation coefficient between temperature and sales.c) Does a linear relationship exist between these variables? Explain to me why or why not this is the case.d) Using excel, calculate the least squares regression equation for this data set. e) Using your equation, predict the soup sales on a day where the temperature is 29 degrees.f) Interpret the slope of this equation.g) Can we use this data set and regression equation to predict the sales on a day when the average temperature is 102 degrees? Why or why not?h) What is the R-squared for this equation? How do you interpret that R-squared?

Match each scatterplot shown below with one of the four specified correlations. a. -0.15 b. -0.76 b c. 0.26 d. 0.91 00 00 a 80 of of 00 80

Give an example of two variables that have a positive linear correlation. Give an example of two variables that have a negative linear correlation. Give an example of two variables that have no correlation. Below is the height in inches and weight in pounds of eleven individuals Height, x 62 63 66 68 70 72 73 74 74 75 75 Weight, y 195 190 250 220 250 255 260 275 280 295 300 x = 65 inches x = 69 inches x = 71 inches

The strength of the correlation is indicated by a number value and the closer that value is to zero, the weaker the correlation. O True O False

Match each scatterplot shown below with one of the four specified correlations Please help

Scenario: Album Sales: A study was done to see whether getting radio airtime and spending money on advertisements accurately predicts the number of album copies sold. A random sample of 200 artists’ albums were tracked on the number of times their songs play on the central radio station, how much money (in thousands) they spent on advertisements, as well as the number (in thousands) of album copies were sold. A record company wanted to determine if there was a positive relationship between album sales and the other two variables (money spent on advertisements and number of albums sold)   What is the Null and alternative hypotheses (based on context of study) in symbols and words:

Which of the following correlations indicates the strongest relationship or association and why? r = .10; r = .03; r = -.35; r = -15

Dr. Erie, a researcher at the Moore County Botany Institute, reported the following correlations. The correlation between pH level of soil and tomato weight is r₁ = -0.4. The correlation between hours of sunlight and tomato weight is r2 = 0.1. According to this information, which of the following statements are true? Select all that apply. Larger tomatoes result from more daily hours of sunlight. Larger tomatoes result from higher soil pH level. Tomato size is related more strongly to hours of sunlight than to soil pH level. None of these are true.