degrees Fahrenheit in a city to predict the number of days children in that city
ID: 2922337 • Letter: D
Question
degrees Fahrenheit in a city to predict the number of days children in that city random sample of 37 cities was selected and the data is displayed in the gh February 21, 2014, of interest was to use the average daily low temperature in missed from school due to weather closings. A 25 20 15 10 5 0 0 10 20 30 40 50 Average Temperature (2 points) Based on the information above, which of the following are correct statements. List the letters of all choices that meet the description (it is possible for there to be more than one correct choice). 1. (A) Average temperature is a lurking variable (B) Days of school missed is a lurking variable. (C) Average temperature is the explanatory variable. (D) Days of school missed is the independent variable. (E) Average temperature is the response variable. (F) Days of school missed is the dependent variable. 2. (6 points) Consider the scatterplot above. Use this scatterplot average temperature and the number of days of school misse lo lessribs sompletely the relat tabove. On the line to the left write the value that you guess the Conside itr is equal to (no calculations are necessary). on line tha r umber of days of school missed -18.16- 0.42(average temperature). Draw this 3. (2 points) Consider the rrelation coefficient r is equal to (no calculations 3. (2 points) dbat gives the linear relationship betiween the average temperature and the number of da that (2 points) The regression 4. regression line on the scatterplot abor o daryExplanation / Answer
1) based on the regression line given in question 3 , average temperture is independent variable and days of school missed is dependent variable. Also , it is given in the question that we want to PREDICT the days of school missed based on the avergae tempertaure. Hence C and F
2) based on the scatterplot , we see that as the average temperature decreases the Days of school missed Increases. Hence they are negatively correlated. When one increases , the other variable decreases
3) There is no data given in the question to plot the regression line , however cut the line at y axis at 18.16 , with the line having a slope of 0.42 . the direction of the line would be from top left to bottom right , following the data points
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