You want to see ifit makes a difference which lane to be in when there is traffic. You randomly observe 204 cars as they pass by on the four lane freeway. The results are displayed in the table: below. Use a level of significance of a=0.01. a. Complete the rest of the tabie by filing in the expected frequencies: Frequency of Cars in Each Lane Outcome Frequency Expected Frequency Lane 1 71 Lane 2 57 Lane 3 38 Lane 4 38 b. What is the correct statistical test to use? Select an answer e What are the null'and alternative hypotheses? Ho: O The traffic and lanes are dependent. O The distribution of traffic is uniform. O The distribution of traffic is not uniform. O The traffic and lanes are independent.

You want to see ifit makes a difference which lane to be in when there is traffic. You randomly observe 204 cars as they pass by on the four lane freeway. The results are displayed in the table: below. Use a level of significance of a=0.01. a. Complete the rest of the tabie by filing in the expected frequencies: Frequency of Cars in Each Lane Outcome Frequency Expected Frequency Lane 1 71 Lane 2 57 Lane 3 38 Lane 4 38 b. What is the correct statistical test to use? Select an answer e What are the null'and alternative hypotheses? Ho: O The traffic and lanes are dependent. O The distribution of traffic is uniform. O The distribution of traffic is not uniform. O The traffic and lanes are independent.

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Description: You want to see ifit makes a difference which lane to be in when there is traffie. You randomlyobserve 204 cars as they pass by on the four lane freeway. The results are displayed in the table:below. Use a level of significance of a= 0.01.a. Complet

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

You want to see ifit makes a difference which lane to be in when there is traffie. You randomly
observe 204 cars as they pass by on the four lane freeway. The results are displayed in the table:
below. Use a level of significance of a= 0.01.
a. Complete the rest of the table by filling in the expected frequencies:
Frequency of Cars in Each Lane
Outcome Frequency Expected Frequency
Lane 1
71
Lane 2 57
Lane 3
38
Lane 4
38
b. What is the correct statistical test to use?
Select an answer
C What are the null 'and alternative hypotheses?
Ho:
O The traffic and lanes are dependent.
O The distribution of traffic is uniform.
O The distribution of trafficis not uniform.
O The traffic and lanes are independent.
The tralfic and lanes are Independent.
he distritutionaftraffic isnH uniform
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O The distribution of traffic is not uniform.
Ô The traffic and lanes are dependent.
O The distribution of traffic is uniform.
d. The degrees of freedom =
{Please show your answer to three decimal places.)
e. The test-statistic for this data
(Please show your answer to four decimal places.)
1. The p-value for this sample = |
g The p-value is Select an answer
h. Based on this, we should Select an answer vị
L Thus, the final conclusion is.
There is sufficient evidence to conclude that the distribution of trafficis not uniform.
O There is insufficient evidence to conclude that traffic and lanes are dependent.
O There is sufficient evidence to conclude that traffic and lanes are dependent.
O There is insufficient evidence to conclude that the distribution of traffic is not uniform.
O There is sufficient evidence to conclude thatthe distribution of traffic is uniform.
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