The following table shows the selling​ prices, in thousands of​ dollars, and the square footages of five randomly selected houses recently sold by a real estate company. The data have a sample correlation​ coefficient, rounded to three decimal​ places, of 0.652. Using alpha equals 0.01 and the data given​ below, test the significance of the population correlation coefficient between a​ house's selling price and its square footage. What conclusions can you​ draw? Selling_Price Square_Footage 253 2725 191 1825 258 2193 163 2105 242 2358 What is the​ p-value?

What effect does an outlier have on a correlation coefficient? Would it increase, decrease or stay the same?

Listed below are the amounts of bills for dinner and the amounts of the tips that were left. Construct a​ scatterplot, find the value of the linear correlation coefficient​ r, and find the​ P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Use a significance level of α=0.01. If everyone were to tip with the same​ percentage, what should be the value of​ r?   Bill​ (dollars) 31.65 53.83 87.10 103.64 60.34 109.80   Tip​ (dollars) 3.74 5.76 14.73 16.86 7.44 20.73   1. The linear correlation coefficient is r=   2.  What are the null and alternative​ hypotheses?   3. The test statistic is t=   4. The P-Value is P=

A food truck owner recorded the temperature at noon, in degrees Fahrenheit, and the number of bowls of soup sold during the lunch hour for a random sample of 5 days. The data are shown in the following table. Temperature (degrees Fahrenheit) 57 75 43 68 67 Number sold 17 12 20 8 13 The mean temperature of the sample is 62 degrees Fahrenheit, and the mean number sold is 14. What is the correlation between the temperature and the number sold? A -0.85 B -0.68 0.68 D 0.73 E 0.85

Consider the relationship between the number of bids an item on eBay received and the item's selling price. The following is a sample of 5 items sold through an auction. Price in Dollars 29 35 41 44 47 Number of Bids 10 11 12 13 14 Step 2 of 3: Estimate the correlation in words: positive, negative, no correlation. Copy Data

The accompanying table lists the ages of acting award winners matched by the years in which the awards were won. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Should we expect that there would be a correlation? Use a significance level of a=0.05. Click the icon to view the ages of the award winners. Construct a scatterplot. Choose the correct graph below. A. 20- 20 E 70 OB. 70- 20+ 20 70 Best Actress (years) The linear correlation coefficient is r= (Round to three decimal places as nee Best Actress (years) Best Actresses and Best Actors Best Actress 28 31 30 64 31 Best Actor 44 39 37 43 49 33 46 47 56 OC. COD. Q 70- 20 20 Best Actress (years) 30 59 23 42 53 442 52 39 56 44 34 70 20 20 70 Best Actress (years)

The accompanying table lists the ages of acting award winners matched by the years in which the awards were won. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Should we expect that there would be a correlation? Use a significance level of a = 0.01. Click the icon to view the ages of the award winners. Construct a scatterplot. Choose the correct graph below. OA. 70- Best Actor (years) 20+ 20 Q [ 70 Best Actress (years) The linear correlation coefficient is r= ☐ (Round to three decimal places as needed.). B. OC. Q 70- 70- Q 20- 20 20- 70 20 70 Best Actress (years) Best Actress (years) Best Actresses and Best Actors Best Actress 29 29 28 57 31 32 45 28 63 22 42 51D Best Actor 45 39 39 47 51 49 64 48 38 55 43 34 O D. 70- Q G 20 20 70 Best Actress (years)

Listed below are amounts of bills for dinner and the amounts of the tips that were left. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Use a significance level of a = 0.05. If everyone were to tip with the same percentage, what should be the value of r? Bill (dollars) Tip (dollars) 69 Construct a scatterplot. Choose the correct graph below. O A. 25- 04 30 1.6 Bill Amount (S) 30.39 49.64 84.71 94.16 62.06 101.95 6.07 8.67 11.03 12.99 9.31 13.46 120 Q ✔ The linear correlation coefficient is r= (Round to three decimal places as needed.) Determine the null and alternative hypotheses. Ho: P H₁: p (Type integers or decimals. Do not round.) The test statistic is t = (Round to two decimal places as needed.) The P-value is (Round to three decimal places as needed.) Because the P-value of the linear correlation…

Based on the scatter plot below on data from Central Harlem, would you estimate the correlation coefficient to be positive, negative, or close to 0? Select the correct correlation and corresponding explanation. Household Income vs. Serious Crime Rate (per 1,000 residents) CentralHarlem Data Scatter Plot: 22- 21- 20- 19- 18- 17 16- 15 32 34 36 38 40 42 Household_Income (thousands) Positive; As the household income increases, the serious crime rate decreases. A. Negative; As the household income increases, the serious crime rate decreases. B. Positive; As the household income increases, the serious crime rate also increases. OC. Negative; As the household income increases, the serious crime rate also increases. D. Close to 0; There is no linear correlation between household income and serious crime rate. E. A Moving to another question will save this response. Question 24 of 25 MacBook Air Serious crime_rate

the accompanying table shows the ages​ (in years) of 11 children and the numbers of words in their vocabulary.  Age, x    Vocabulary size, y1    32    2603    5904    11005    19006    25003    7305    22002    2504    13006    2400 1. Calculate the sample correlation coefficient r. 2. Describe the type of​ correlation, if​ any, and interpret the correlation in the context of the data. 3. Use the table of critical values for the Pearson correlation coefficient to make a conclusion about the correlation coefficient. Let α=0.01.