1. Manufacturers often include "suggested retail prices" with goods that are shipped from the factories. However, retailers are not bound by these suggested prices; A manufacturer of a brand of food processor with a suggested retail price of $89.95, is curious to know if the mean price charged among all retailers is below the suggested retail price. He randomly samples 28 retail stores and records the price at which each is selling the food processor. The sample results find a mean of $87.72 and a standard deviation of $5.10. A. Do the data provide sufficient evidence to conclude that the true mean price of the food processor is below the suggested retail price? Test at the .05 level of signific B. What type of error might you have made in part A? Explain fully.

Refer to the data set:(-1, 2), (1, 3), (1, 5), (2, 7), (3, 8), (4, 11)Part a: Make a scatter plot and determine which type of model best fits the data.Part b: Find the regression equation.Part c: Use the equation from Part b to determine y when x = 10

How much did Patricia earn last week

Figure out the equation that makes this design on the graphing calculator.

Fill in the blank. You are doing a study for a non-profit group helping at-risk children in your city. Suppose you know that 14.2% of the children in your city live in poverty. This percentage is an example of a You are doing a study for a non-profit group helping at-risk children in your city. Suppose you know that 14.2% of the children in your city live in poverty. This percentage is an example of a population parameter. sample statistic.

the box plot represents the average temperature in seattle for each day in august. what is the interquartile range of the data

Fill in the blanks. The variable is the variable whose value can be explained by the OA. predictor; response OB. response; lurking C. lurking; response O D. response; predictor variable.

DIRECTIONS: The table below shows the age t (in years) and the number of hours h slept per day by 24 infants who were less than one year old.    Find the LSRL for the data set. Inerpret a and b. Make a prediction for the amount of sleep for an average 9 month old.    Make a prediction for the amount of sleep for an average 18 month old. Provide a scatterplot and graph of the LSRL Interpret the values of the correlation coefficient and the coefficient of determination.   Age (t) Sleep (h) 0.03 15.0 0.05 15.8 0.05 16.4 0.08 16.2 0.11 14.8 0.19 14.7 0.21 14.5 0.26 15.4 0.34 15.2 0.35 15.3 0.35 14.4 0.44 13.9 0.52 13.9 0.69 13.2 0.70 14.1 0.75 14.2 0.80 13.4 0.82 13.2 0.86 13.9 0.91 13.1 0.94 13.7 0.97 12.7 0.98 13.7 0.98 13.6

Make a scatter plot of the data and determine which type of model best fits the data. (-3,-1), (-2,0), (-1,1), (0,2), (1,3), (2,4)

SCUBA divers have maximum dive times they cannot exceed when going to different depths. The data in the table below show different depths with the maximum dive times in minutes. (Comma separated lists of the data are also provided below the table to ease in copying the data to R.) Depth in Feet (x) 50 60 70 80 90 100 x: 50, 60, 70, 80, 90, 100 y: 179, 166, 150, 138, 124, 110 Maximum Dive Time in Minutes (y) 179 166 150 138 124 110 1. Find the best fit line for the data. y = + x 2. Graph the scatter plot of the data together with the best fit line using R. (This portion of the problem is not graded.) 3. Predict the maximum dive time at a depth of 23 feet. Question Help: D Post to forum