A geographer conducts a study of the relationship between the level of economic development of a nation measured in thousands of dollars for per capita GDP) and the birth rate (average number of children per adult woman). For one analysis of the data, a part of the computer printout reports Statistic Value SE Correlation -0.460 0.170 Explain how to interpret the reported value of the correlation. b. Can you tell whether the sign of the slope in the corresponding prediction equation would be positive or negative? Why? c. Suppose the prediction equation were ý=5.6-0.1x. Interpret the slope, and show how to find the predicted

Describe the relationship between x and y in a positive correlation and in a negative correlation. In the calculations for the correlation coefficient, what does the sum of products of deviations measure and how is this number used in the calculation of r?

Below is a scatterplot of a student’s SAT score and their college GPA. Suppose we want to decide if a student’s SAT score and their GPA are linearly related.  What does this scatterplot tell us of the relationship?  Support your answer. SAT score_GPA scatterplot.pdf

Suppose that you are interested in the relationship between Reading and Writing scores. (a)  Provide the scatterplot for the association between Reading and Writing scores. Based on the scatterplot, do you expect Reading to be correlated with Writing? If so, based only on the plot, would you expect the correlation to be positive or negative? Explain your answer. (b)  Report the value of the correlation between Reading and Writing scores, and whether it is statistically significant. Do these results agree with your expectations from part (a)? RDG WRTG 34 44 47 36 42 59 39 41 36 49 50 46 63 65 44 52 47 41 44 50 50 62 44 41 47 40 42 59 42 41 47 41 60 65 39 49 57 54 73 65 47 46 39 44 35 39 39 41 48 49 31 41 52 63 47 54 36 44 47 44 34 46 52 57 42 40 37 44 44 33 71 58 47 46 42 33 42 36 47 41 52 54 52 54 39 39 31 41 60 54 47 31 39 28 42 36 47 57 42 49 36 41 50 33 34 34 55 55 28 46…

10) Using advertised prices for used Ford Escorts a linear model for the relationship between a car's age and its price is found. The regression has an R2-87.4%. Write a sentence summarizing what R2 says about this regression. A) The age of the car explains 9.35% of the variation in price. B) The price of the car explains 12.6% of the variation in age. C) The age of the car explains 87.4% of the variation in price. D) The price of the car explains 87.4% of the variation in age. E) The age of the car explains 12.6% of the variation in price. Solve. Round to two decimal places if necessary. 11) At one college, 68% of students have credit cards. A credit card company, looking for new customers, sets up a booth at the college. If they pick students at random, how many students should they expect to talk to before finding one who does not have a credit card? A) 32 B) 3.13 D) 68 C) 0.32 E) 1.47

Medical records indicate that people with more education tend to live longer; the correlation is 0.91. The slope of the linear model that predicts lifespan from years of education suggests that on average people, tend to live 1.46 extra years for each additional year of education they have. The slope of the line that would predict lifespan from years of education is:   1.46 91     146 0.91

Below is a table showing the relationship between age and bone density of a typical healthy adult male.   Age (years)   25 35 45 55 65 75 85 Bone density (mg/cm²) 1165 1135 1085 1060 1015 975 910     Using your line of best fit find the equation for this line. Describe the correlation between the two variables and what conclusions can you make from this set of data?   Using graph plotted extrapolate to find the bone density of a 90 years old typical adult.

The linear correlation between violent crime rate and percentage of the population that has a cell phone is −0.918 for years since 1995. Do you believe that increasing the percentage of the population that has a cell phone will decrease the violent crime​ rate? What might be a lurking variable between percentage of the population with a cell phone and violent crime​ rate?       Question content area bottom Part 1 Will increasing the percentage of the population that has a cell phone decrease the violent crime​? Part 2 What might be a lurking variable between percentage of the population with a cell phone and violent crime​ rate?

State the regression equation and use it to predict taxes for a house with lot size 10K.

A linear model was fit to predict weekly Sales of frozen pizza (in pounds) from the average Price ($/unit) charged by a sample of stores in a city in 39 weeks over a three -year period. The average Sales were 63, 200 pounds (SD = 10, 670 pounds), and the correlation between Price and Sales was -0.529. If the Price in a particular week was two SD higher than the mean Price, how much pizza would you predict was sold that week?