### Exercise 25**Figure 61**The scatterplot and the model in Figure 61 describe the association between years and Apple employment (in millions).#### Graph Description- **Title**: Years versus Apple Employment- **X-axis**: Labeled "Years since 2005," with values ranging from 0 to 14.- **Y-axis**: Labeled "Employment (millions)," with values ranging from 0 to 140.- **Data Points**: A series of blue dots representing employment data over time.- **Trend Line**: A red line indicating the trend.#### Tasks**a.** Determine the direction of the association. What does that mean in this situation?**b.** Estimate the rate of change of Apple employment.(Source: Apple)

Answered: Image /qna-images/answer/21b132a1-4a0c-413a-83c9-f93bfb9efdb4.jpg

Answered: 25. The scatterplot and the model in…

Algebra and Trigonometry (6th Edition)

6th Edition

ISBN:9780134463216

Author:Robert F. Blitzer

Publisher:Robert F. Blitzer

ChapterP: Prerequisites: Fundamental Concepts Of Algebra

Section: Chapter Questions

Problem 1MCCP: In Exercises 1-25, simplify the given expression or perform the indicated operation (and simplify,...

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メ 6) The scatter plot shows the time spent texting and the time spent exercising by each of 24 students last week. Also shown is the line of best fit for the data. Fill in the blanks below. 13 12 11- 10 Time spent exercising 7. (in hours) 6 - 5. 4 3. 2. 3. 10 11 Time spent texting (in hours) (a) For these 24 students, as the time spent texting increases, the time spent exercising tends to (b) For these 24 students, there is ? correlation between time spent texting and time spent exercising. (c) Using the line of best fit, we would predict that a student texting for 6 hours would exercise for approximately ? hours.
A grocery store manager did a study to look at the relationship between the amount of time (in minutes) customers spend in the store and the amount of money (in dollars) they spend. The results of the survey are shown below. Time 11 13 23 12 21 24 24 24 17 Money 59 71 81 43 89 99 108 81 71 Use the model to predict the amount of money spent by a customer who spends 19 minutes at the store.Dollars spent = (Please round your answer to the nearest whole number.)
ověr a Number of People (thousands) Day 1 9. 13 17 What is the meaning of the rate of change for the data? A The park had an decrease in attendance of 4,000 people per day. B. The park had an decrease in attendance of 4 people per day. C. The park had a increase in attendance of 4,000 people per day. D. The park had a increase in attendance of 4 people per day. endar To Do Notifications
is the plot has a trend?
Does this graph have trends and/or seasonality? What forecasting method is suitable for this data?
Example: Emergency call to the fire department over the past 15 weeks are the following: 20, 27, 25, 22, 18, 21, 26, 19, 16, 28, 25, 26, 17, 23, 27 Use exponential smoothing with a smoothing constant of 0.5 to forecast the number of the calls for the next week. Solution: No, of Calls (At) Forecast (Actual time] Week (Ft) 20 2 27 3. 25 22 18 21 7 26 8. 19 6. 16 10 28 11 25 12 26 13 17 14 23 15 27 Find F16. Ft-1 + a(At-1- Ft-1) %3D | Forecast = previous forecast + a(Actual previous period - previous forecast) Put F1 = A1 = 20 %3D F2 = F, + a(A, - F,) = 20 +0.5(20-20) = 20 F3 = 23.5 %3D
Below is data collected over 6 specific years. The data collected is the Consumer Price Index (CPI) and the cost of a slice of tuna. We would like to build a model using the CPI to predict the cost of a slice of pizza in a given year. Year 1960 1973 1986 1995 2002 2003 CPI (x) 30.2 48.3 112.3 162.2 191.9 197.8 Cost of a slice of tuna(y) 0.15 0.35 1.00 1.25 1.75 2.00 Plot the data. Are we justified in creating a Linear Regression model to predict the price of a pizza slice using the CPI? Why or why not? Calculate the descriptive statistics. Calculate the sums of squares Calculate the slope, intercept, and correlation. What is this correlation value telling us? Assemble the prediction equation, and interpret the slope within the context of the problem. State the hypotheses for the hypothesis test for regression.
Q3 A manufacturer has plotted product sales over the past four weeks. Use a linear trend line to generate a forecast for week 5. T (week) Y (Sales) 1 2300 2 2400 3 2200 4 2600
The data in the table below represents the percentage of a country's population aged 20 years or older whose age is x who do not have a high school diploma. Complete parts (a) through (c) below. Age, a Pecentage without a H. S. Diploma, P 20 30 40 50 60 70 13.1 11.5 10.5 13.5 22.3 29.8 (a) Using a graphing utility, draw a scatter diagram of the data treating age as the independent variable. What type of relation appears to exist between age and percentage of the population without a high school diploma? Which graph below is a scatter diagram of the data? A. В. OC. D. P 40- AP 40- 70- 70- a a P 20+ 0+ 20 20- 0+ 20 70 40 70 40 Use the graph to determine which sentence below best describes the relation between age and percentage of the population without a high school diploma. A. There appears to be a linear relation between age and percentage. B. There does not appear to be any relation between age and percentage. O C. There appears to be a quadratic relation between age and percentage.
The survivorship curve indicated by the graph best represents a curve, and is common in populations of Life Stage O a. Type l, marine invertebrates O b. Type Il, fishes Oc. Type l, humans o d. Type II, birds O e. Type l, plants % Surviving
Help with 4
2. A professor wants to see how much students learn over the course of a semester. A pre test is given before the class begins to see what students know ahead of time, and the same test is given at the end of the semester to see what students know at the end. The data are below. Test for an improvement at the a = 0.05 level. Did scores increase? How much did scores increase? Pretest 90 Posttest Xp 89 60 66 95 99 93 91 95 100 64 67 89 91 90 95 95 94 83 89 75 82 87 92 82 83 85 82 88 93 66 90 69 90 93 100 86 95 91 96

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