2.39. WP State what you would plot to get a straight line if experimental (x, y) data are to be correlated by the following relations, and what the slopes and intercepts would be in terms of the relation parameters. If you could equally well use two different kinds of plots (e.g., rectangular or semilog), state what you would plot in each case. [The solution to Part (a) is given as an example.] a. y? = ae-b/æ. Solution: Construct a semilog plot of y? versus 1/x or a plot of In (y²) versus 1/x on rectangular coordinates. Slope = -b, intercept = In a. b. y? = mx³ c. 1/In (y – 3) (1+ avx)/b d. (y+ 1)° = [a(» – 3)"] * е. у 3 еxp (a/т +b) f. xy = 10[a(x²+y*)+8] g. y = [ax + b/x]¬ 10 a(a²+y²)+b] -1

2.39. WP State what you would plot to get a straight line if experimental (x, y) data are to be correlated by the following relations, and what the slopes and intercepts would be in terms of the relation parameters. If you could equally well use two different kinds of plots (e.g., rectangular or semilog), state what you would plot in each case. [The solution to Part (a) is given as an example.] a. y? = ae-b/æ. Solution: Construct a semilog plot of y? versus 1/x or a plot of In (y²) versus 1/x on rectangular coordinates. Slope = -b, intercept = In a. b. y? = mx³ c. 1/In (y – 3) (1+ avx)/b d. (y+ 1)° = [a(» – 3)"] * е. у 3 еxp (a/т +b) f. xy = 10[a(x²+y*)+8] g. y = [ax + b/x]¬ 10 a(a²+y²)+b] -1

Algebra & Trigonometry with Analytic Geometry

13th Edition

ISBN:9781133382119

Author:Swokowski

Publisher:Swokowski

Chapter7: Analytic Trigonometry

Section7.6: The Inverse Trigonometric Functions

Problem 94E

See similar textbooks

Similar questions

Refer image to questions -What are the degrees of freedom? (choose from below) 45 43 71 47 - What is the correct decision for this test? (choose from below) Since p-value > 0.05, do not reject H0 Since p-value < 0.05, reject H0 Since p-value > 0.05, reject H0 Since p-value < 0.05, do not reject H0 - An appropriate conclusion for this test is (choose from below) -There is a significant positive linear relation between the first and second pulse rates of those who did not run on the spot -There is a significant negative linear relation between the first and second pulse rates of those who did not run on the spot -There is no significant linear relation between the first and second pulse rates of those who did not run on the spot -There is not enough evidence of a linear relation between the first and second pulse rates of those who did not run on the spot
A major credit card company is interested in whether there is a linear relationship between its internal rating of a customer’s credit risk and that of an independent rating agency. The company collected a random sample of 200 customers and used the data to test the claim that there is a linear relationship. The following hypotheses were used to test the claim. H0:β1=0Ha:β1≠0 The test yielded a t-value of 3.34 with a corresponding p-value of 0.001. Which of the following is the correct interpretation of the p-value? If the alternative hypothesis is true, the probability of observing a test statistic at least as extreme as 3.34 is 0.001. If the alternative hypothesis is true, the probability of observing a test statistic at least as extreme as 3.34 is 0.001. A If the alternative hypothesis is true, the probability of observing a test statistic of 3.34 or greater is 0.001. If the alternative hypothesis is true, the probability of observing a test statistic of 3.34 or greater…
Which of the following statements is NOT true? a.If the correlation coefficent, rr, is negative, then the slope of the regression line must always be negative. b.For variables x and y, the value of the correlation coefficent will not change c.if the units of x and y are changed, (i.e., if both x and y are changed from say inches to meters) d.If r≠0r≠0 , then a significant linear correlation will exist between the two variables e.The value of the correlation coefficient must be within the interval: −1≤r≤1
The data below are the temperatures on randomly chosen days during the summer and the number of employee absences at a local company on those days. Test the claim, at the α = 0.05 level of significance, that a linear relation exists between the two variables, Apply classical and p-value approaches. Show step1-step3. Input β1 as "beta1" or "β1". Do NOT input as "b1". Temperature x 72 85 91 94 100 80 90 78 99 number of absences y 3 7 10 10 8 9 4 15 15 Round critical value and test statistic to nearest hundredth. (0.125 would be entered 0.13) Round p-value to nearest ten-thousandth. (0.14275 would be entered 0.1428)
6) The line of best fit through a set of data isy=36.704+0.985xy=36.704+0.985xAccording to this equation, what is the predicted value of the dependent variable when the independent variable has value 30?y = Round to 1 decimal place.
The accompanying data were compiled by the admissions office of a certain college during the past 5 years. The data relate the number of college brochures and follow-up letters (x) sent to a preselected list of high school juniors who took the PSAT and the number of completed applications (y) received from these students (both measured in thousands). Brochures Sent, x 1.1 2 3.8 5 6.2 Applications Completed, y 0.3 0.5 1 1.25 1.6 (a) Derive an equation of the straight line that passes through the points (2, 0.5) and (5, 1.25).y = (b) Use this equation to predict the number of completed applications that might be expected if 8000 brochures and follow-up letters are sent out during the next year. applications
Consider the following set of ordered pairs. Assuming that the regression line is y= 2.205 + 0.645x and that the SSE = 7.7180, test to determine if the slope is not equal to zero using a= 0.10. I am having trouble, please help!
Test the null hypothesis that the slope is zero versus the two-sided alternative in the following setting using the alpha=0.05 signifiance level. n=20, yhat=28.5+1.4x, and SEb1=0.65
If the coefficient of determination (R2) value is 0.99, it means the 99% of ____________ of the observed y-values of are explained by the __________ of the predicted y-values, and only 1% remains unexplained.
Given are five observations for two variables, x and y. xi 5 13 7 21 19 yi 59 42 55 10 29 -select your answer- choices: a. (A, B, C, D) the different graphs are being attached b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables? There appears to be a (positive, negative) linear relationship between x and y. c. Try to approximate the relationship between x and y by drawing a straight line through the data. (Many different straight lines can be drawn, Only one straight line can be drawn, A straight line cannot be drawn) to provide a linear approximation of the relationship between x and y. D & E questions are being attached. Thank you!
The data below are the temperatures on randomly chosen days during the summer and the number of employee absences at a local company on those days. Test the claim, at the α = 0.05 level of significance, that a linear relation exists between the two variables, Apply classical and traditional approaches. Show step1-step3. Input β 1 as "beta1" or "β 1". Do not input as "b1". Temperature x 72 85 91 94 100 80 90 78 99 number of absences y 3 7 10 10 8 9 4 15 15
Determine the best (according to sum-of-squares-measure) curve y = Axb, through the dataabove.Transformed equation ln(y) = ln(A) + b ln(x)orY = a + bX.