The accompanying table shows the ages (in years) of 11 children and the numbers of words in their vocabulary. Complete parts (a) through (d) below.Click here to view the data table. Click here to view the table of critical values for the Pearson correlation coefficient.r= 0.973(Round to three decimal places as needed.)(c) Describe the type of correlation, if any, and interpret the correlation in the context of the dața.There isa strong positive linear correlation.Interpret the correlation. Choose the correct answer below.O A. Aging causes the number of words in children's vocabulary to increase.O B. Based on the correlation, there does not appear to be any relationship between children's ages and the number of words in their vocabulary.O C. Based on the correlation, there does not appear to be a linear relationship between children's ages and the number of words in their vocabularyOD. Aging causes the number of words in children's vocabulary to decrease.E. As age increases, the number of words in children's vocabulary tends to increase.O F. As age increases, the number of words in children's vocabulary tends to decrease. The accompanying table shows the ages (in years) of 11 children and the numbers of words in their vocabulary. Complete parts (a) through (d) below.Click here to view the data table, Click here to view the table of critical values for the Pearson correlation coefficient.r= 0.973Data Table(Round to three decimal places as needed(c) Describe the type of correlation, if any,Age, xVocabulary size, yThere isa strong positive linear correla15260Interpret the correlation. Choose the corred6101100O A. Aging causes the number of words2200O B. Based on the correlation, there doewords in their vocabulary.2600OC. Based on the correlation, there doe3730of words in their vocabulary2400D. Aging causes the number of words270O E. As age increases, the number of w41300O F. As age increases, the number of w2400View anear allCheck answe

Answered: The accompanying table shows the ages…

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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You wish to determine if there is a linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.05 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 21 22 39 21 38 18 23 22 79 36 42 22 65 29 Ho: p = 0 Ha: p= 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is O Less than (or equal to) a Greater than a The p-value leads to a decision to O Reject Ho O Accept Ho O Do Not Reject Ho The conclusion is O There is insufficient evidence to make a conclusion about the linear correlation between driver age and number of driver deaths. There is a significant linear correlation between driver age and number of driver deaths. O There is a significant negative linear correlation between driver age and number of driver deaths. O There is a significant positive linear correlation…
The table lists weights (pounds) and highway mileage amounts (mpg) for seven automobiles. Use the sample data to construct a scatterplot Use the first variable for the x-axis. Based on the scatterplot, what do you conclude about a linear correlation? 2425 Weight (Ib) Highway (mpg) 2725 2875 3480 4070 4090 3125 34 33 30 25 24 36 31 Which scatterplot below shows the data? O A. OB. C. O D. 40- 40- 40 20+ 2000 20- 2000 Weight (Ib) 20어 2000 20- 2000 Weight (Ib) 5000 5000 5000 5000 Weight (Ib) Weight (Ib) Is there a linear relationship between weight and highway mileage? O A. No, there appears to be no relationship. O B. Yes, as the weight increases the highway mileage increases. O C. No, there appears to be a relationship, but it is not linear. Click to select your answer. 4:21 PM a 17 梦 * v 6/4/2021 W 0 門 e Type here to search Chp ins prt sc delet fg ho ト f8 144 f6 10 f5 f4 IOI esc back & #3 $4 4 T. 6, 00 %24 (6 d) AamH 3. (B dw) Am
(e)
Fully explain the issues and problems with the below correlational data. Focus on the data in the highlighted box versus the rest of the data. Do not try to explain the data, but rather focus on the statistical issues and problems. IF YOU CAN'T SEE THE IMAGE HERE. PLEASE GO TO THIS LINK Linke 10 6. 8. 7. 5. 4. 10 20 30 40 50 60 70 80 90 100 Age Enjoyment of Hip-Hop
The data below are the ages and annual pharmacy b ills (in dollars) of 9 randomly selected employees. Calculate the linear correlation coefficient.Age, x: 30, 33, 37, 40, 43, 45, 49, 53, 57Pharmacy bill ($), y: 119, 123, 126, 134, 145, 148, 151, 153, 155A. 0.890B. 0.908C. 0.998D. 0.960
The accompanying table shows the ages (in years) of 11 children and the numbers of words in their vocabulary. Complete parts (a) through (d) below. Click here to view the data table. Click here to view the table of critical values for the Pearson correlation coefficient. Data table Critical values for the pearson correlation coefficient (a) Display the data O A. Age, x Vocabulary size, y Critical Values for the 1 6 3000- 2400- 1800- 1200- Pearson Correlation Coefficient 210 3 590 4 1300 The correlation is significant when the absolute value of is greater than the value in the table. 600- 2200 6 4 6 0 2 Age (year 2600 a = 0.05 0.950 a = 0.01 0.990 4 6 8 years) 3 680 4 2100 0.878 0.959 (b) Calculate the sa 280 6 0.811 0.917 7 0.754 0.875 4 1100 0.834 0.798 8 0.707 (Round to three de 6. 2300 0.666 10 0.632 0.765 (c) Describe the ty 11 0.602 0.735 12 0.576 0.708 There is 13 0.553 0.684 Done 0.661 0.532 0.514 0.497 Print 14 15 0.641 Interpret the correla 16 0.623 17 0.482 0.606 O A. As age…
Do all Please calculate: Parameters a and b Correlation coefficient Determination coefficient Write correlation equation Visualise data in Scatter chart Provide explanation of results Year Sales, MEUR (Yi) Employees with higher education (Xi) 2010 70 10 2011 90 12 2012 100 15 2013 80 13 2014 110 17 2015 120 20 2016 150 25 2017 200 25 2018 200 25
The data below shows the selling price (in hundred thousands) and the list price (in hundred thousands) of homes sold. Construct a scatterplot, find the value of the linear correlation coefficient r, and P-value using a = 0.05. Is there sufficient evidence to conclude that there is a linear correlation between the two variables? Selling Price (x) List Price (y) H₁: p#0 400 412 Construct a scatterplot. Choose the correct graph below. 301 315 376 387 434 440 459 488 H₁ p > 0 477 480 319 324 352 368 417 434 330 341
Answer
Which of the following is an appropriate research question for a correlation? Group of answer choices Is there a relationship between weather and mood? Does cold weather impact mood? Does drinking milkshakes make children happy? Does exercising reduce weight?
Stan measured the circumference of his classmates' heads and compared it with their current grade in Math. The results are in the given table. Head (cm) Grade 55 23 53 92 57 84 56 88 55 97 53 87 54 72 57 64 57 91 Is there a strong correlation in this data set? How do you know? Yes, there is a strong correlation because the slope is 126.5. No, there is NOT a strong correlation because the correlation coefficient is -0.89, which is close to -1.
The numbers of pass attempts and passing yards for seven professional quarterback for a recent year are listed in the table below. Round all answers to the nearest 1000th. Pass attempts (x) 449 565 528 197 670 351 218 Passing Yards (y) 3265 4018 3669 1141 5177 2362 1737 Calculate the sample correlation coefficient, r. Describe the type of correlation coefficient and interpret the correlation in the context of the data.

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