Answered: Is there a linear relationship between…

Is there a linear relationship between the two variables? Measles Cases 44 150 62 53 208 Mumps Cases 807 436 2021 2559 357

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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Paragraph Styles 4. Reading is fundamental to a teenager's ability to perform well in school. Assume a researcher is interested in the ability of the number of books read over the summer to predict ACT Reading scores. Using a random sample of 10 random high school students the researchers recorded the number of books read over the summer and the students' ACT Reading scores. Books read over summer (x) ACT Reading score (y) 16 19 17 4 25 4 21 24 6. 21 8 24 27 10 22 Answer the following questions using the SPSS regression analysis OUTPUT (given below): a. From the SPSS regression analysis OUTPUT (given below), write the regression line using the number of books read to predict ACT Reading score. b. What is the predicted ACT Reading score when 5 books are read? C. Does the number of books read significantly predicts ACT at a = 0.05? State your null and alternative hypotheses. d. How much variation in y is explained by this linear regression model? D Focus a IN
Percentage variance and turkey HSD
Based on the hourly incomes (in US dollars) of employees in two different branches at Citibank, which set of incomes has the most variability? You do not have to calculate anything, but you can if you want to. Just take a look at the incomes and determine which set has the most variability based on the definition.
Which statistical analysis is needed to address this research question: Relationship commitment will change over time. One sample t-test Two sample t-test ANOVA Paired sample t-test
The value of the ___________ is used to estimate the value of the population parameter.
There is a strong relationship between heterosexual couples attractiveness scores. Therefore, a researcher wanted to determine if husbands attractiveness score may be predicted from their counterparts’ scores. Below are couples attractiveness ratings. Observation Wife (X) Husband (Y) 1 11 14 2 6 7 3 16 15 4 4 7 5 1 3 6 10 9 7 5 9 8 3 8 Complete the following ANOVA table Source SS DF MS F SSreg SSres SStotal
Time to review: The following table presents the time taken to review articles that were submitted for publication to a particular journal during a recent year. A few articles took longer than months to review; these are omitted from the table. Consider the data to be a population. Time (Months) Number of Articles 0-0.9 40 1.0-1.9 19 2.0-2.9 15 3.0- 3.9 20 4.0-4.9 12 5.0- 5.9 11 Send data to Excel (a) Approximate the variance of the times. Round the answer to at least two decimal places. The variance is (b) Approximate the standard deviation of the times. Round the answer to at least two decimal places. The standard deviation is
Question 24 Which statement is true about the data set 3, 4, 5, 6, 7, 7, 10? O mean = mode O mean> mode O mean = median O mean < median Previous 93
otected View - Saved to this PC Search View Help 12. The city council is considering a law that would ban smoking in all public facilities. A sample has been selected from the community and tested for of the ordinance. Is there a statistically significant relationship between age and support for the anti-smoking law? Use the five step model as a guide and write a sentence or two interpreting your results. support Age More than 40 Less than 40 Support: For 145 78 223 Against 103 248 169 247 272 495 A. Use probabilities to determine if these two variable are independent or dependent P (Less than 40) 3D P(Less than 40 | For)= P(Less than 40| Against) = Are age and support for the anti-smoking law independent? (Yes independent/No = not independent) B. Conduct a hypothesis test using an alpha of .05 that these variables are i
Looking for the answers and explanation to questions 1,2 and 3 below. Histogram is attached so no need to run it. Your boss asks you to gather all data regarding pounds of waste across all areas identified. You go through the store archives and find data over the past 100 weeks. The weekly pounds of waste is in the chart below (treat this as population data). She wants to know if the data is normally distributed and for you to explain process variability to her. You decide to run a histogram to visually inspect for data normality. 1.) Explain to your boss the histogram and the “shape” of the curve. 2.) Is it normally distributed? 3.) Does it appear that there is high or low variability in the waste numbers? Explain to your boss. Pounds of Wasted Food 493 521 500 461 500 523 554 499 514 508 527 505 470 523 518 479 463 483 477 478 494 494 480 522 543 472 538 502 486 508 513 486 487 478 519 481…
Frequency 344.7 389.1 394.3 411.8 412.1 431.9 433.5 445 447.4 452.3 465.4 466 469.2 469.2 469.2 469.8 470.6 471.7 471.8 474.9 483 483.1 485 490.4 494.8 495.8 496.8 496.8 500 506.8 512.5 516.6 520.1 520.4 524.8 534.8 545.3 547.4 558.1 556.4 558.1 558.1 580.6 564.4 572.4 577.4 585 586.2 587.8 588.2 593.8 606.1 607.8 611.4 = 18 16 14 12 10 8 6 4 2 300 350 400 450 500 Find the first quartile for this data set. Q₁ length (cm) = 550 600 650 Find the third quartile for this data set. Q3² = Find the interquartile range for this data set. IQR = = Find the lower fence separating outliers from usual values. Fence Low Find the upper fence separating outliers from usual values. Fence high
Box plots (Excel)– Analyze each of these cycle time data but on the same chart: C7, C8, C9. That means one chart showing three different box plots, with a single conclusion that addresses all three. Interpret outside value, mean score, N spread, Fence, upper lower and upper outer fences, adjacent, and outside and far out value. C7 C8 C9 19.98211 20.7142 20.21992 20.01223 20.65907 20.00799 20.02408 20.6437 20.02974 19.94534 20.45958 19.94026 19.86814 20.63716 19.796 20.18784 20.65365 20.01327 19.92074 20.54906 20.01064 20.0778 20.5228 20.07752 19.88045 20.47224 19.95005 20.08633 20.61675 20.13076 19.99881 20.62622 20.06755 20.04184 20.42231 20.13078 19.7936 20.61609 19.88701 19.93159 20.52705 19.87559 20.19998 20.58901 19.88053 20.18833 20.49057 19.9302 20.12368 20.68086 19.9738 19.91343 20.57999 19.8936 20.1602 20.34386 20.02487 20.09396 20.62949 20.09329 20.11419 20.66649 20.00717 19.9063 20.71718 20.04545 20.12964 20.43237 19.95537…