(b) Compute the value of the correlation coefficient. Round your answer to at least three decimal places.Part 3 of 5(c) State the hypotheses.H :O=0ロチロOロPart: 3/5Part 4 of 5(d) Test the significance of the correlation coefficient at a=0.05, usingThe Critical Values for the PPMC Table.Critical value(s): ±(Choose one) v the null hypothesis. Forest Fires and Acres Burned An environmentalist wants to determine the relationships between the numbers (in thousands) of forest fires over the yearand the number (in hundred thousands) of acres burned. The data for 6 recent years are shown.Number of fires x69 58 47 84 62 57Number of acres burned y42 1926 51 15 30Send data to Excel

Answered: (b) Compute the value of the…

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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(a) Draw a scatter diagram of the data. Compute the linear correlation coefficient. The linear correlation coefficient for the four pieces of data is (Round to three decimal places as needed.) Part 2 (b) Draw a scatter diagram of the data with the additional data point (10.3,9.3). Compute the linear correlation coefficient with the additional data point. The linear correlation coefficient for the five pieces of data is (Round to three decimal places as needed.) part 3 Comment on the effect the additional data point has on the linear correlation coefficient. Explain why correlations should always be reported with scatter diagrams.
The relationship between two variables partialling out the effect that a third variable has on one of those variables can be expressed using a: a. Partial correlation O b. Point-biserial correlation Oc. Semi-partial correlation Od. Bivariate correlation
Find: The linear correlation coefficient is r= The critical values are r=
Q1-Q5: a) Find the value of the line ar correlation coefficient r b) Find the critical values ofr from table A-6 using x= 0.05 c) Determine whether there is sufficient evidence to support a claim of a linear correlation Between the two variables. d) Find the regression equation, e) Letting the first variable be the predietor (x) variable, find the indicated predieted value. Q1. Altitude and Temperature: Altitude 3 10 14 22 28 31 33 ( thousands of feet) Temperature ( °F) 57 37 24 -5 -30 -41 -54 At 6.327 thousand feet, the author recorded the temperature. Find the best predieted temperature at that altitude. How does the result compare to the actual recorded value of 48°F?
Determining significance of the correlation coefficient. Step 1: State the hypotheses. Ho: p = 0; H₁: p = 0 Step 2: Find the critical values. Two-tailed, Table F Step 3: Compute the test value. t = r freedom d.f. = n-2 Step 4: Make the decision. Step 5: Summarize the results. 54 n-2 1-2 with degrees of For each exercise, draw the scatter plot, determine if r is statistically significant, find the equation of the regression line and find the y'value for the specified xvalue. Remember that no regression should be done when ris not significant. 8.2 1. New Broadway productions and seasonal attendance are as follows. No. Of 67 62 54 61 Productions Attendance 7.4 (million) Find y' when x = 48 new productions. n(Exy) - (Ex) (Ey) √[n(Ex²) - (Ex)²][n(Ey²) — (Ey)²] CALC: STAT →Tests →LinRegTTest 7.1 r = 8.8 9.6 60 11 50 8.4 37 7.4
V53980 V2 Example 8.13. Calculate correlation coefficient r(x, y) from the following data : n = 10, Ex = 140, Ey = 150, {(x-10)2 = 180, E(y-15)2 = 215, E(x-10) (y- 15) = 60 [Delhi Univ. B.Com. (Hons.), 2007]
Please finish the R code to conduct the hypothesis testing. I need the code for the p-value for the F test, tstat, and the p value for tstat. Write the conclusion to the hypothesis testing once completed. # Example 11.1# simple linear regression# H0: B=0 (there is no linear correlation)# H1: B≠0 (there is a linear correlation)data <- data.frame(estriol=c(7,9,9,12,14,16,16,14,16,16,17,19,21,24,15,16,17,25,27,15,15,15,16,19,18,17,18,20,22,25,24),birthweight=c(25,25,25,27,27,27,24,30,30,31,30,31,30,28,32,32,32,32,34,34,34,35,35,34,35,36,37,38,40,39,43))linear <- lm(birthweight~estriol, data = data)summary(linear)# This gives the results for a and b and the F statistic. # Call:# lm(formula = birthweight ~ estriol, data = data)# # Residuals:# Min 1Q Median 3Q Max # -8.1200 -2.0381 -0.0381 3.3537 6.8800 # # Coefficients:# Estimate Std. Error t value Pr(>|t|) # (Intercept) 21.5234 2.6204 8.214 4.68e-09 ***# estriol 0.6082 0.1468 4.143…
You run a regression analysis on a bivariate set of data (n = 110). You obtain the regression equation y = – 3.546x 4.393 0.248 (which is significant at a = 0.01). You want to predict with a correlation coefficient of r = - what value (on average) for the explanatory variable will give you a value of 100 on the response variable. What is the predicted explanatory value? X = (Report answer accurate to one decimal place.)
Q1. Altitude and Temperature:Altitude( thousands of feet)3 10 14 22 28 31 33Temperature( 0?)57 37 24 −5 −30 −41 −54At 6.327 thousand feet, the author recorded the temperature. Find the best predicted temperatureat that altitude. How does the result compare to the actual recorded value of 480?? a) Find the value of the linear correlation coefficient ?b) Find the critical values of r from table A-6 using ∝= 0.05c) Determine whether there is sufficient evidence to support a claim of a linear correlationBetween the two variables.d) Find the regression equation,e) Letting the first variable be the predictor (x) variable, find the indicated predicted value.
Book Pages (x) Price (y) A 500 $7.10 B 700 7.60 C 750 9.10 D 590 6.60 E 560 7.60 F 650 7.10 G 475 5.10 (a) Develop a least squares estimated regression line. (Round your numerical values to three decimal places.) (b) Compute the coefficient of determination. (Round your answer to four decimal places.) Explain its meaning. (Give your answer as a percent. Round your answer to two decimal places.) The value of the coefficient of determination tells us that % of the variability in |--?-- ☑ has been explained by the least squares regression equation.
My solution is incorrect
The linear correlation coefficient is r=0.9780.978. (Round to three decimal places as needed.) Determine the null and alternative hypotheses. H0:ρ ____ ______ H1:ρ _____ _______ (Type integers or decimals. Do not round.) The test statistic is t= (Round to two decimal places as needed.) The P-value is (Round to three decimal places as needed.) Because the P-value of the linear correlation coefficient is less than or equal to: the significance level, there is: sufficient evidence to support the claim that there is a linear correlation between bill amounts and tip amounts. If everyone were to tip with the same percentage, then r= (Round to three decimal places as needed.)

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