The following table shows economic development measured in per capita income PCINC.YearPCINCYearPCINC187033919201,040188049019301, 166189059119401,362190074719501, 842191091819602, 123Table 12.7a.What are the independent and dependent variables?The independent variable is theand the dependent variable is theyesarpr pla meb. Which of the following is the correct scatterplat for the data above?25002 2000-a 15001000-A 500-19801920X- year188019401960190025002000-15001000-a 500-188019001920194019601980X- year2500-2000-15001000500188019001920X- year1940196025002000-15001000500188019001920194019601980X-yearaucoM eyndeo ad - d C.Use regression to find the line of best fit and the correlation coefficient.Round your answers to two decimal places.y =18.639x-34631.479r =0.947d.What is the slope of the regression equation? What does it mean?The slope of the regression equation is0.947and it means that per capita incomeby Numberfor each year.increasesе.Use the line of best fit to estimate PCINC for 1900, and for 2000.Round your answers to the nearest integer (dollar).When the year is 1900, y783When the year is 2000, y2447

The given data shows the economic development measured in per capita income PCINC.

Answered: The following table shows economic…

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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2. Calculate the Pearson correlation for the following data X Y 13 915 31 153 174 157 1410 82 16
The following data was collected to explore how the average number of hours a student studies per night and the student's GPA affect their ACT score. The dependent variable is the ACT score, the first independent variable (x1) is the number of hours spent studying, and the second independent variable (x2) is the student's GPA. Effects on ACT Scores Study Hours GPA ACT Score 0 2 17 1 2 20 3 2 25 5 4 26 5 4 26 Copy Data Step 2 of 2: Determine if a statistically significant linear relationship exists between the independent and dependent variables at the 0.05 level of significance. If the relationship is statistically significant, identify the multiple regression equation that best fits the data, rounding the answers to three decimal places. Otherwise, indicate that there is not enough evidence to show that the relationship is statistically significant. Answer How to enter your answer (opens in new window) 2 Points Keypad Keyboard Shortcuts Selecting a checkbox will replace the entered…
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Waiting times (in minutes) of customers at a bank where all customers enter a single waiting line and a bank where customers wait in individual lines at three different teller windows are listed below. Find the coefficient of variation for each of the two sets of data, then compare the variation. Bank A (single line): 6.4 6.7 6.7 6.8 7.1 7.3 7.3 7.6 7.7 7.7 o 4.3 5.3 5.9 6.3 6.7 7.6 7.8 8.5 9.3 9.8 Bank B (individual lines): The coefficient of variation for the waiting times at Bank A is %. (Round to one decimal place as needed.) The coefficient of variation for the waiting times at the Bank B is %. (Round to one decimal place as needed.) Is there a difference in variation between the two data sets? O A. There is no significant difference in the variations. O B. The waiting times at Bank B have considerably less variation than the waiting times at Bank A. O C. The waiting times at Bank A have considerably less variation than the waiting times at Bank B. Ans
D coefficient correlation please. Formula provided.
1. The grades of a class of 9 students on a midterm report and on the final examination are as follows: MR 77 50 71 72 81 94 96 99 67 FE 82 66 78 34 47 85 99 99 68 A. What is the dependent and independent variable? B. Pearson'sr= Interpret: C.r-square = Interpret:
C. Describe the four characteristics of association
Principal components analysis is best suited for O A. none of these B. highly correlated variables C. all variables D. uncorrelated variables
A study was done to look at the relationship between number of vacation days employees take each year and the number of sick days they take each year. The results of the survey are shown below. Vacation Days 5 15 13 3 9 0 3 7 7 14 4 Sick Days 5 5 1 5 4 9 9 6 5 3 9 Use the model to predict the number of sick days taken for an employee who took 3 vacation days this year.Sick Days = ? (Please round your answer to the nearest whole number.) Interpret the slope of the regression line in the context of the question: As x goes up, y goes down. The slope has no practical meaning since a negative number cannot occur with vacation days and sick days. For every additional vacation day taken, employees tend to take on average 0.40 fewer sick days. Interpret the y-intercept in the context of the question: The y-intercept has no practical meaning for this study. If an employee takes no vacation days, then that employee will take 8 sick days. The average number of sick days is…
Weight (lbs.) 173 184 194 214 168 220 188 188 207 167 217 Systolic Blood Pressure 132 143 153 162 154 168 137 149 159 128 1 1. The sample correlation coefficient is _____________
In order to advise students properly, a college advisor is interested in the relationship between a student's GPA and the number of hours the student an average weck. The data are shown in the table. Study Time (in hours) 33 Student GPA 3.2 19 16 2.4 31 3.1 5. 24 2.7 28 2.9 7 1.7 34 3.3 14 2.2 10 35 3.4 11 1.8 Part 1 of 5 (a) Let I represent study time and let y nepresent GPA. Graph the points. Grade Point Average vs. Weekly Study Time Weckly Study Time (hours) Part 2 of 5 (b) Does there appear to be a linear trend? Yes Part: 2/5 Part 3 of 5 (c) use the data points (16, 2.4) and (34, 3 3) to find an eguation of the line through these points. Express numbers as decimas or integers. Write answer in slope-intercept form (y = MI+ b). The equation is GPA
The population of a certain city is shown in the following table during 1910 to 1950. Year 1910 1920 1930 1940 1950 Рорulation (in thousands) 22.6 45 26 48 60 Find the population increase between I. 1918 to 1920 II. 1932 to 1936 III. 1947 to 1950

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