The accompanying data came from a study of collusion in bidding within the construction industry. No. Bidders No. Contracts 2 3 4 5 6 7 8 9 10 11 USE SALT 8 20 26 18 12 8 6 7 4 3 (a) What proportion of the contracts involved at most five bidders? At least five bidders? (Round your answers to four decimal places.) at most five bidders at least five bidders X X (b) What proportion of the contracts involved between five and 10 bidders, inclusive? Strictly between five and 10 bidders? (Round your answers to four decimal places.) between five and 10 bidders, inclusive strictly between five and 10 bidders X X

The accompanying data came from a study of collusion in bidding within the construction industry. No. Bidders No. Contracts 2 3 4 5 6 7 8 9 10 11 USE SALT 8 20 26 18 12 8 6 7 4 3 (a) What proportion of the contracts involved at most five bidders? At least five bidders? (Round your answers to four decimal places.) at most five bidders at least five bidders X X (b) What proportion of the contracts involved between five and 10 bidders, inclusive? Strictly between five and 10 bidders? (Round your answers to four decimal places.) between five and 10 bidders, inclusive strictly between five and 10 bidders X X

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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3. Below are the numbers of flights on time and delayed for Alaska Airlines at five airports in one month. On time 497 221 212 503 Seattle 1841 (a)Among the flights to Los Angeles, what percent of flights were delayed? (b)What percent of delayed flights were not flying to Los Angeles? Los Angeles Phoenix San Diego San Francisco Delayed 62 12 20 102 305
2.2 1 help with statistics question
14. Match these values of r with the accompanying scatterplots: 0.363, 0.994, - 0.747, 0.747, and 1. Click the icon to view the scatterplots. Match the values of r to the scatterplots. Scatterplot 1, r= (1) %3D Scatterplot 2, r= (2) %3D Scatterplot 3, r= (3) Scatterplot 4, r= (4) – Scatterplot 5, r= (5). 6: Scatterplots Scatterplot 1 Scatterplot 2 Scatterplot 3 157 14- 6- 13- > 4- 12- 11- 2- 10 0 0.2 0.4 0.6 0.8 0. 0.2 0.4 0.6 0.8 1 1 0.2 0.4 0.6 0.8 1 Scatterplot 4 Scatterplot 5 6- 6- .. 4- > 4- 2- 2- 0. 0.2 0.4 0.6 0.8 1 0. 0.2 0.4 0.6 0.8 1 (1) O 0.994 O 0.747 0 1 O - 0.747 O 0.363 (2) O 0.994 O - 0.747 O 0.363 O 1 O 0.747 (3) O 0.994 O 0.747 O 1 O 0.747 O 0.363 (4) O 0.994 O -0.747 O 0.747 O 0.363 (5) O 0.363 O-0.747 0 1 O 0.747 6- 4.
Dif-in-Dif requires: 1. Identical characteristics between treatment and control groups II. Panel or repeated cross-sectional data III. Time-varying unobservables to be similar across treatment and control groups IV. Time-invariant unobservables to be similar across treatment and control groups O l and IV I and III None of the other answers is correct III and IV O Il and III
2) Below is an unidentified table of values: x 78 85 92 100 85 89 93 99 100 84 y 1. What is the key issue if these data are test grades of subjects before and after formal instruction? ("Is the instruction effective, as indicated by higher y scores?" See Section 9-4.) 2. What is the key issue if these data are reasoning tests for a sample of men (x) and a separate sample of women (y)? ("Does the population of men have the same mean as the population of women?" See Section 9-3.) What is the key issue if each pair represents a math reasoning score x and a starting salary y in thousands of dollars? ("Is the starting salary associated with math reasoning?" See this chapter.) 3.
An article studied differences between expert and consumer ratings by considering medal ratings for wines, which could be gold (G), silver (S), or bronze (B). Three categories were then established. 1. Rating is the same [(G, G), (B, B), (S, S)) Rating differs by one medal [(G, S), (S, G), (S, B), (B, S)] 3. Rating differs by two medals [(G, B), (B, G)] The observed frequencies for these three categories were 63, 104, and 41, respectively. On the hypothesis of equally likely expert ratings and consumer ratings being assigned completely by chance, each of the nine medal pairs has probability 1/9. Carry out an appropriate chi-squared test using a significance level of 0.10. LUSE SALT State the appropriate hypotheses. O Ho: P₁ = P₂ = P3 H₂: at least one p, +== 13 O Ho: P₁ P₂P3== H₂: at least one p, * Pio OH₁²P₁ = P₂ = P3 = = 1 H₂: at least one p, *== 4 O H₁² P₁ = P₂ = ₁P3 = ² Ho: P2 H₁: at least one p, * P10 Calculate the test statistic. (Round your answer to two decimal places.) What can…
he table below shows the mark scheme for three students doing Business and Economic Calculus. Grades in % Course requirements % Kwesi Onaji Chevaneese Zaim Quiz 10% Sectional 30% Assignment 20% Final Exam 40% 60 83 74 92 96 85 86 51 88 90 79 60 94 88 76 81 Which student got the highest overall grade? a. Kwesi b. Onaji c. Chevaneese d. Zaim Instruction:
1.The Prevalence of having health insurance (as a decimal) for 1 (Table 4 box b. above) is: 2. The Prevalence of having health insurance (as a decimal) for 2 (Table 4 box e. above) is: 3.The Prevalence of having health insurance (as a percentage) for 1 (Table 4 box c. above) is: 4.The Prevalence of having health insurance (as a Percentage) for 2 (Table 4 box f. above) is:
Given below are the analysis of variance results from a stat software display comparing sample data for the meanmileage for 4 different types of cars. Assume that you want to use a 0.05 significance level in testing the null hypothesisthat the different samples come from cars with the same mileage. What can you conclude about the equality of the population means?Source DF SS MS F pFactor 3 13.500 4.500 5.17 0.011Error 16 13.925 0.870Total 19 27.425 12)What is the null and alternative hypothesis for this scenari?Based on this One Way Anova software analysis, would you reject of fail to reject the nul hypothesis?What does this result mean in context?