---### Transcription and Explanation of Data and Graph**Data Table:**| Temperature (°F) | Coffee Sales ($) ||------------------|------------------|| 42.0 | 1980.2 || 52.0 | 1856.9 || 62.0 | 1804.2 || 39.1 | 2308.9 || 49.4 | 2198.9 || 47.0 | 1966.6 || 48.7 | 2120.9 || 81.4 | 1549.6 || 69.0 | 1748.2 || 75.3 | 1981.8 || 57.6 | 1617.9 || 59.8 | 1962.2 |**Graph Explanation:**- **Title:** Not provided.- **Axes:** - **X-axis:** Temperature (in degrees Fahrenheit), ranging approximately from 40 to 90. - **Y-axis:** Coffee Sales (in dollars), ranging from 1200 to 2400.- **Data Points:** The graph is a scatter plot with data points marked as blue crosses.- **Figure 1:** Shows a general inverse relationship, indicating that as the temperature increases, coffee sales tend to decrease.**Correlation Coefficient:**The value of the sample correlation coefficient $ r $ for these data is approximately $-0.634$. This indicates a moderate negative correlation between temperature and coffee sales.**Instructions for Analysis:**Carry your intermediate computations to at least four decimal places, and round your answers as specified below.- (a) What is the value of the slope of the least-squares regression line for these data? - **Round your answer to at least two decimal places.** - [ ] (Write your answer here)- (b) What is the value of the $ y $-intercept of the least-squares regression line for these data? - **Round your answer to at least two decimal places.** - [ ] (Write your answer here)Feel free to consult a list of formulas if necessary to complete the computations.--- **Coffee Sales and Temperature Analysis**Managers of an outdoor coffee stand in Coast City are examining the relationship between hot coffee sales and daily temperature, hoping to predict a day's total coffee sales from the maximum temperature that day. The bivariate data values for the coffee sales (denoted by $ y $, in dollars) and the maximum temperature (denoted by $ x $, in degrees Fahrenheit) for each of sixteen randomly selected days during the past year are given below. These data are plotted in the scatter plot in Figure 1.| Temperature, $ x $ (in degrees Fahrenheit) | Coffee sales, $ y $ (in dollars) ||----------------------------------------------|------------------------------------|| 44.6 | 1772.4 || 76.5 | 1534.3 || 72.3 | 1654.0 || 38.8 | 1946.0 || 71.3 | 1951.6 || 55.2 | 1826.9 || 62.0 | 1804.2 || 39.1 | 2308.9 || 49.4 | 2198.9 || 47.0 | 1966.6 || 48.7 | 2120.9 || 81.4 | 1549.6 || 69.0 | 1748.2 || 75.3 | 1981.8 || 57.6 | 1617.9 || 59.8 | 1962.2 |**Figure 1: Scatter Plot Analysis**The scatter plot visualizes the relationship between temperature (in degrees Fahrenheit) and coffee sales (in dollars). On the x-axis is the temperature ranging from 30 to 90 degrees, and on the y-axis is coffee sales ranging from 1200 to 2400 dollars.Observations from the scatter plot include:- As temperature increases, there tends to be a decrease in coffee sales.- This inverse relationship suggests that cooler temperatures may result in higher coffee sales.- The data points are scattered, showing variability which could be useful for more detailed statistical analysis.This analysis is part of understanding consumer behavior concerning weather conditions and can assist in

In this case Temperature (x) is the independent variable and Coffee sales (y) is the dependent…

62.0 1804.2 1600- 39.1 2308.9 1400- 49.4 2198.9 1200- 47.0 1966.6 48.7 2120.9 40 so 60 70 80 90 81.4 1549.6 Temperature (in degrees Fahrenheit) 69.0 1748.2 Figure 1 75.3 1981.8 57.6 1617.9 59.8 1962.2 The value of the sample correlation coefficient r for these data is approximately - 0.634. Answer the following. Carry your intermediate computations to at least four decimal places, and round your answers as specified below. (If necessary, consult a list of formulas.) (a) What is the value of the slope of the least-squares regression line for these data? Round your answer to at least two decimal places. (b) What is the value of the y-intercept of the least-squares regression line for these data? Round your answer to at least two decimal places. Coffee op ui)

62.0 1804.2 1600- 39.1 2308.9 1400- 49.4 2198.9 1200- 47.0 1966.6 48.7 2120.9 40 so 60 70 80 90 81.4 1549.6 Temperature (in degrees Fahrenheit) 69.0 1748.2 Figure 1 75.3 1981.8 57.6 1617.9 59.8 1962.2 The value of the sample correlation coefficient r for these data is approximately - 0.634. Answer the following. Carry your intermediate computations to at least four decimal places, and round your answers as specified below. (If necessary, consult a list of formulas.) (a) What is the value of the slope of the least-squares regression line for these data? Round your answer to at least two decimal places. (b) What is the value of the y-intercept of the least-squares regression line for these data? Round your answer to at least two decimal places. Coffee op ui)

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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