15) After declining over the past century, the percentage of men aged 65 and older in the workforce hasbegun to rise in recent years, as shown by the following tableYearPercent of men 65 orolder in the workforce192055.6193054194041.8195045.8096197033.126.8198016.306000,201017.720.5202023.3A) use the regression feature on your calculator to find a cubic function (use CubicReg) that models thedata LET x=0 correspond to the year 1920 and change all the other years accordinglyb) Use your answer in part a to the rate the at which the percent of men aged 65 and older in theworkforce was changing in 1965, 2015 and 2021punn

As per the question we are given th following data table : And we have to find the best fit cubic…

Answered: 15) After declining over the past…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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Years Height (cm) 0.9 0.79 2.0 3.98 2.1 4.81 4.0 11.41 4.8 29.72 5.2 24.2 6.2 26.81 9.0 91.47 9.1 129.45 Use automatic linear regression (e.g. using Excel or Sheets) to find a line of best fit, with the Years as the "x" values and the Height (cm) as "y" values. Explain exactly what you did.
answer 6
9. A wildlife researcher is interested in predicting a mammal’s lifespan (in years) based on its average number of hours of sleep per night. Data was obtained from a large random sample of mammals, and the regression equation turned out as follows: Predicted lifespan = 36.93 – 1.64 (average hours of sleep) Which one of the following statements is a correct interpretation of this equation? 1. Approximately 1.64% of the variability in lifespan can be explained by the regression equation. 2. As lifespan increases by one year, average hours of sleep is predicted to decrease by 1.64 hours. 3. As lifespan increases by one year, average hours of sleep is predicted to increase by 36.93 hours. 4. As average hours of sleep increases by one hour, lifespan is predicted to increase by 36.93 years. 5. As average hours of sleep increases by one hour, lifespan is predicted to decrease by 1.64 years.
Q.1 The Conference Board produces a Consumer Confidence Index (CCI) that reflects people’s feelings about general business conditions, employment opportunities, and their own income prospects. Some researchers feel that consumer confidence is a function of median household income. Shown here are CCIs for 9 years and median household incomes for the same 9 years published by the U. S. Bureau of the Census. CCCI Income ($1000) a) Determine the equation of the regression line 8 37.415 used to predict the CCI from the median household 68.3 35.015 income 90.5 36.770 62.6 35.237…
Which one of the following statements is true? When predicting one quantitative variable based on another, the variable you are trying to predict should always go on the x-axis of the scatterplot. The intercept in a regression equation can never negative. The correlation coefficient has no units. A very strong relationship between variables can result in a value of r that is larger than 1. A correlation coefficient can only range in value from 0 to 1.
Based on the firm's data and the regression line, answer the following. A. From the regression equation, what is the predicted percentage increase in sales when the advertising campaign cost is 1.50 million dollars? Round your answer to two or more decimal places. B. From the regression equation, what is the predicted percentage increase in sales when the advertising campaign cost is 1.62 million dollars? Round your answer to two or more decimal places.
Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary = 10,896.07 + 2755.34 (Education) + 773.89 (Experience) Suppose two employees at the company have been working there for five years. One has a bachelor's degree (8.years of education) and one has a master's degree ( 10 years of education). How much more money would we expect the employee with a master's degree to make?
The following 10 questions are pertaining to this Data (Please input this data into an Excel worksheet and do not forget to include a column for the time period Year QTR SUBSCRIBERS 2000 1. 205 2. 400 200 4. 229 2001 236 2. 219 211 200 2002 280 2. 275 3. 261 4. 322 2003 1. 500 2. 230 310 4. 400 2004 1. 325 2. 241 3. 379 4. 316 1 pts The Trend Value (using Regression) for Quarter 1 of 2002 is: O 235.94 O 355.98 O 229.23 O 277.95
The data presented is a multiple logistic regression analysis and the models are shown below. In the models below, the data are coded as follows: p = the proportion of children with a diagnosis of ADHD, Child Exposed and Father’s Diagnosis are coded as 1 = yes and 0 = no. What is the odds ratio adjusted for father’s diagnosis? (Hint: Use only the appropriate model to find the odds ratio) (1) = –2.216 + 1.480 Child exposed (2) Father with diagnosis: = –1.665 + 1.297 Child exposed (3) Father without diagnosis: = –2.343 + 0.823 Child exposed (4) = –2.398 + 1.501 Child exposed + 0.906 Father’s diagnosis
Consider the following hypothetical regression: FRIES = 22.5 + 0.08*TRAFFIC + 9.1*COUPON? + -1.1*TEMP where FRIES is the number of pounds of fries a restaurant sells in a week, TRAFFIC is the number of people who walked by the restaurant that week (foot traffic), COUPON? is a dummy variable of if the restaurant offered a coupon or not that week (1=coupon, 0=no coupon); and TEMP is the average high that week, measured in Fahrenheit. All variables are statistically significant. If the average high is expected to be 4 degrees warmer next week, how should FRIES change? 1 Increase by 18.1 pounds 2 Decrease by 4.4 pounds 3 It is impossible to tell without knowing the values of TRAFFIC and COUPON?. 4 Increase by 4.4 pounds 5 Increase by 26.9 pounds
Which of the following applies the concept of “layering” to increase the sensitivity of a research analysis? Group of answer choices a. Chi-square Contingency Tables b. Binary Logistic Regression c. Regression d. Answers 1 and 2 only e. Answers 1, 2 and 3
A psychologist wants to determine if there is a linear relationship between the number of hours a person goes without sleep and the number of mistakes he/she makes on a simple test. The following data is recorded. a. Give a list of the residual values b. Look at the residual plot. Comment on what the residual plot tells you about the data . c. If appropriate , test the correlation using an alpha level of 0.05 . (Show all 6 steps!!!!)

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