Based on the following calculator output, determine the inter-quartile range of thedataset.1-Var-Statsa = 281.571428571Ex = 1971Ex? = 557049Sx = 18.5818651993ox = 17.2034642928n = 7minX258Q1= 269Med283Q3 = 296maxX = 313

Interquatile Range is given by, IQR= Q3-Q1 Where Q3 is the third Quartile of the data And Q1 is…

Based on the following calculator output, determine the inter-quartile range of the dataset. 1-Var-Stats T = 281.571428571 Σα-1971 Ex? = 557049 Sx = 18.5818651993 ox = 17.2034642928 n = 7 minX 258 Q1 269 Med 283 Q3 296 maxX = 313

Based on the following calculator output, determine the inter-quartile range of the dataset. 1-Var-Stats T = 281.571428571 Σα-1971 Ex? = 557049 Sx = 18.5818651993 ox = 17.2034642928 n = 7 minX 258 Q1 269 Med 283 Q3 296 maxX = 313

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

A physical therapist wanted to know whether the mean step pulse of men was less than the mean step pulse of women. She randomly selected 54 men and 70 women to participate in the study. Each subject was required to step up and down a 6-inch platform. The pulse of each subject was then recorded. The following results were obtained. Two sample T for Men vs Women N Mean StDev SE Mean Men Women 98% CI for mu Men - mu Women (- 12.20, - 1.00) T-Test mu Men = mu Women (vs H2 O C. Ho: H1 = H2; Ha: H1 #H2 (b) Identify the P-value and state the researcher's conclusion if the level of significance was a = 0.01. What is the P-value? P-value =
tled1.tst 1 / 1 dent/Downloads/Math%201332%20Activity%20%236.pdf X 1 Find the mean, mode, median and midrange. 2) 2 Score Frequency 3 4 5 X 6 Math 1332 Activity #6.pdf: 6231- 7 8 9 10 119% + B HLSATOOGEE f 1 5 4 7 6 10 12 11
1. Was a dependent or independent t-test used to analyze the data? How do you know?
The Cadet is a popular model of sport utility vehicle, known for its relatively high resale value. The bivariate data given below were taken from a sample of fifteen Cadets, each bought new two years ago, and each sold used within the past month. For each Cadet in the sample, we have listed both the mileage x (in thousands of miles) that the Cadet had on its odometer at the time it was sold used and the price y (in thousands of dollars) at which the Cadet was sold used. The least-squares regression line for these data has equation y = 40.86-0.45x. This line is shown in the scatter plot below. Mileage, x (in thousands) 29.7 27.8 26.8 24.2 21.1 23.0 24.3 15.4 37.7 23.6 34.4 27.8 23.5 20.9 259 Used selling price, y (in thousands of dollars) 27.4 29.4 31.2 30.1 31.7 31.7 27.2 34.2 23.4 28.2 26.3 26.5 33.7 30.6 267 Used selling price (in thousands of dollars) 40- 35+ 30- 25- 20 THIS 15 X 20 X X X 30 Mileagex (in thousands) X 35 40
Use the Stata output below to answer the following question. The data used in this analysis is from a sample of airlines. The variables used are: fare-avg price of a one-way fare, in dollars dist- distance of the flight, in miles .reg fare ldist. Source Model Residual 551.391705 Total lfare SS ldist _cons 875.094374 df The OLS results suggest that 1 323.702668 120024315 4,594 MS Coef. Std. Err. 4,595 190444913 Number of obs F(1, 4594) Prob > F R-squared Adj R-squared Root MSE t P>|t| .4025646 .0077517 51.93 0.000 2.399834 .0521601 46.01 0.000 4,596 2696.98 0.0000 0.3699 0.3698 .34645 [95% Conf. Intervall .3873676 .4177617 2.297575 2.502093 a 1% increase in distance is associated with approximately a $.40 increase in the price of the fare. a 1% increase in distance is associated with approximately a .40% increase in the price of the fare. a 1% increase in distance is associated with approximately a 40 % increase in the price of the fare. None of the above.
The following output comes from regression using the actual HW9 scores and the Final test scores from intro stats one semester. Sample size: 50R (correlation coefficient) = 0.3658R-sq = 0.1338Estimate of error standard deviation: 10.36256Parameter estimates: Parameter Estimate Std. Err. DF T-Stat P-Value Intercept 43.558118 11.1716 48 3.899 0.0003 Slope 0.360048 0.132225 48 2.723 0.009 Assume no assumptions are violated. Form a 87% Confidence interval for how much your final is supposed to increase for each problem done on homework 9.Use 5 decimal places
It has been estimated that the 1991 G-car obtains a mean of 35 miles per gallon on the highway, and the company that manufactures the car claims that it exceeds the estimate in highway driving. To support its assertion, the company randomly selects 49 1991 G-cars and records the mileage obtained for each car over a driving course similar to that used to obtain the estimate. The following data resulted: x = 36.5 miles per gallon, s = 7 miles per gallon. %3D a. Find the observed significance level for testing Ho: u= 35 vs. Ha: u> 35. %3D b. For what value of significance level a, you will reject the null hypothesis.
Devise a hypotheses for the research question: Is there singificant correlation between students height and typical amount of sleep a student gets per night? Identify the appropriate statistical test using alpha = 0.05. Perform the statistical test. Use descriptive statistics to describe the variables both numerically and graphically. Height (whole inches) Sleep (minutes) 60 360 62 400 66 420 68 440 68 540 70 480 72 320 75 440 66 360 63 420 69 420 75 390 69 360 67 480 69 360 73 360 69 480 70 420 68 360 63 480 69 270 68 360 71 420 71 360 62 420
From the graphs displayed, is there evidence to suggest that there is a positive linear relationship between Square Feet and Bathrooms, for the population of real estate represented by this sample? Be sure to provide numeric support in your answer.
The Cadet is a popular model of sport utility vehicle, known for its relatively high resale value. The bivariate data given below were taken from a sample of sixteen Cadets, each bought new two years ago, and each sold used within the past month. For each Cadet in the sample, we have listed both the mileage x (in thousands of miles) that the Cadet had on its odometer at the time it was sold used and the price y (in thousands of dollars) at which the Cadet was sold used. The least-squares regression line for these data has equation Ŷ=42.80-0.53x. This line is shown in the scatter plot below. (The 2nd picture contains the rest of the data as it would not fit in the first pic and it includes the question as well.)