The table shows data on the number of visitors to the UK in a month, v (1000s), and the amount of money they spent, m (£ millions), for each of 8 months. Number of visitors 2450 2480 2540 2420 2350 2290 2400 2460 v (1000s) Amount of money spent 1370| 1350 1400 1330 1270 1210 1330 1350 m (£ millions) The correlation coefficient between m and v is 0.962 a. Give a reason to support fitting a regression model of the form m = a + bv to these data. b. Summary statistics are: v = 2423.75, m = 1326.25, s, = 77.9995421, sm = 1326.25, R = 0.962 For a regression model of the form m = a + bv . Find the value of b (the slope) correct to two decimal places. c. Now calculate a (the intercept) to calculate the regression model. d. Interpreting the value of b, each additional visitor spends £ e. Using the equation calculated in part c, estimate the amount of money spent when the number of visitors to the UK in a month is 2,500,000

The table shows data on the number of visitors to the UK in a month, v (1000s), and the amount of money they spent, m (£ millions), for each of 8 months. Number of visitors 2450 2480 2540 2420 2350 2290 2400 2460 v (1000s) Amount of money spent 1370| 1350 1400 1330 1270 1210 1330 1350 m (£ millions) The correlation coefficient between m and v is 0.962 a. Give a reason to support fitting a regression model of the form m = a + bv to these data. b. Summary statistics are: v = 2423.75, m = 1326.25, s, = 77.9995421, sm = 1326.25, R = 0.962 For a regression model of the form m = a + bv . Find the value of b (the slope) correct to two decimal places. c. Now calculate a (the intercept) to calculate the regression model. d. Interpreting the value of b, each additional visitor spends £ e. Using the equation calculated in part c, estimate the amount of money spent when the number of visitors to the UK in a month is 2,500,000

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Description: The table shows data on the number of visitors to the UK in a month, v (1000s), and the amount ofmoney they spent, m (£ millions), for each of 8 months.Number of visitors2450 2480 2540 2420 2350 2290 2400 2460v (1000s)Amount of money spent 1370| 135

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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Concept explainers

Inverse Normal Distribution

The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.

Mean, Median, Mode

It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.

Z-Scores

A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.

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Question

The table shows data on the number of visitors to the UK in a month, v (1000s), and the amount of
money they spent, m (£ millions), for each of 8 months.
Number of visitors
2450 2480 2540 2420 2350 2290 2400 2460
v (1000s)
Amount of money spent 1370| 1350 1400 1330 1270 1210 1330 1350
m (£ millions)
The correlation coefficient between m and v is 0.962
a. Give a reason to support fitting a regression model of the form m = a + bv to these data.
b. Summary statistics are:
v = 2423.75, m = 1326.25, s, = 77.9995421, sm = 1326.25, R = 0.962
For a regression model of the form m = a + bv . Find the value of b (the slope) correct to two
decimal places.
c. Now calculate a (the intercept) to calculate the regression model.
d. Interpreting the value of b, each additional visitor spends £
e. Using the equation calculated in part c, estimate the amount of money spent when the number
of visitors to the UK in a month is 2,500,000

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