A sixth-grade teacher believes that there is a relationship between his students’ IQ scores (y) and the numbers of hours (x) they spend watching television each week. The following table shows a random sample of 7 sixth-grade students. y 125 116 97 114 85 107 105 x 5 10 30 16 41 28 21  Which one is the explanatory variable? And which one is the response variable?  Assuming that a linear relationship exists between the IQ score of a student and the number of hours he/she spends watching television each week, use computer software to find the least squares line relating y to x. Give a scatterplot along with the least-squares regression line. (Just copy the graph from the monitor onto the paper. You don’t need to print out the graph.) Then interpret the value of the slope of the least squares line in the above context.

Statistics Question

Suppose we are interested in comparing the proportion of male students who smoke to the proportion of female students who smoke. We have a random sample of 150 students (60 males and 90 females) that includes two variables: Smoke = "yes" or "no" and Gender = "female (F)" or "male (M)". The two-way table below summarizes the results. Smoke = Yes Smoke = No Sample Size 60 90 Gender = M Gender = F Reference: 3-15-No Tech 9 9 51 81 Describe how to use the data to construct a bootstrap distribution. What value should be recorded for each of the bootstrap samples.

Suppose two variables are negatively correlated. Does the response variable increase or decrease as the explanatory variable increases?

Suppose the observational units in a study are the patients arriving at an emergency room on a given day, Nov 11, 2019.  Number of patients that arrive before noon     is a qualitative variable       is a quantitative variable       is not a variable

In a survey conducted by a wedding planning website, 1206 maried or engaged women were asked about the importance of a bended knee when making a marriage proposal. Among the 1206 respondents, 62% said that the bended knee was essential. Complete parts (a) through (d). a. What is the exact value that is 62% of 1206 survey respondents? The exact value is (Type an integer or a decimal. Do not round.)

Q1

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

4. time to try out multiple predictor variables. take a look at the data shown here, where the outcome is becoming a great chef. we suspect that variables such as number of years of experience cooking, level of formal culinary education, and number of different positions (sous chef, pasta station, etc.) all contribute to rankings or scores on the great chef test. a. which are the best predictors of a chef’s score? b. what score can you expect from a person with 12 years of experience and a level 2 education who has held five positions?

You wish to determine if there is a linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.01 and round all values to 4 decimal places. Driver Age 65 69 48 37 49 27 62 64 Ho: p = 0 Ha: p = 0 r= Find the p-value p-value= Number of Driver Deaths per 100,000 22 22 34 Find the Linear Correlation Coefficient The p-value is Greater than a Less than (or equal to) a 23 28 20 The p-value leads to a decision to O Do Not Reject Ho O Accept Ho O Reject Ho 33 33 The conclusion is O There is a significant negative linear correlation between driver age and number of driver deaths. There is a significant linear correlation between driver age and number of driver deaths. O There is insufficient evidence to make a conclusion about the linear correlation between driver age and number of driver deaths. O There is a significant positive linear correlation…