The average number of accidents at controlled intersections per year is 5.8. Is this average a different number for intersections with cameras installed? The 46 randomly observed intersections with cameras installed had an average of 6.1 accidents per year and the standard deviation was 0.83. What can be concluded at the αα = 0.01 level of significance? The p-value = (Please show your answer to 4 decimal places.) The p-value is ? α Based on this, we should the null hypothesis. Thus, the final conclusion is that ... The data suggest that the sample mean is not significantly different from 5.8 at αα = 0.01, so there is statistically insignificant evidence to conclude that the sample mean number of accidents per year at intersections with cameras installed is different from 6.1 accidents. The data suggest that the population mean is not significantly different from 5.8 at αα = 0.01, so there is statistically insignificant evidence to conclude that the population mean number of accidents per year at intersections with cameras installed is different from 5.8 accidents. The data suggest that the populaton mean is significantly different from 5.8 at αα = 0.01, so there is statistically significant evidence to conclude that the population mean number of accidents per year at intersections with cameras installed is different from 5.8 accidents. Interpret the p-value in the context of the study. There is a 1.81758026% chance that the population mean number of accidents per year at intersections with cameras installed is not equal to 5.8. If the population mean number of accidents per year at intersections with cameras installed is 5.8 and if another 46 intersections with cameras installed are observed then there would be a 1.81758026% chance that the sample mean for these 46 intersections with cameras installed would either be less than 6 or greater than 6.1. There is a 1.81758026% chance of a Type I error. If the population mean number of accidents per year at intersections with cameras installed is 5.8 and if another 46 intersections with cameras installed are observed then there would be a 1.81758026% chance that the population mean would either be less than 6 or greater than 6.1. Interpret the level of significance in the context of the study. There is a 1% chance that the population mean number of accidents per year at intersections with cameras installed is different from 5.8. If the population population mean number of accidents per year at intersections with cameras installed is different from 5.8 and if another 46 intersections with cameras installed are observed then there would be a 1% chance that we would end up falsely concluding that the population mean number of accidents per year at intersections with cameras installed is equal to 5.8. There is a 1% chance that you will get in a car accident, so please wear a seat belt. If the population mean number of accidents per year at intersections with cameras installed is 5.8 and if another 46 intersections with cameras installed are observed then there would be a 1% chance that we would end up falsely concluding that the population mean number of accidents per year at intersections with cameras installed is different from 5.8.

The average number of accidents at controlled intersections per year is 5.8. Is this average a different number for intersections with cameras installed? The 46 randomly observed intersections with cameras installed had an average of 6.1 accidents per year and the standard deviation was 0.83. What can be concluded at the αα = 0.01 level of significance? The p-value = (Please show your answer to 4 decimal places.) The p-value is ? α Based on this, we should the null hypothesis. Thus, the final conclusion is that ... The data suggest that the sample mean is not significantly different from 5.8 at αα = 0.01, so there is statistically insignificant evidence to conclude that the sample mean number of accidents per year at intersections with cameras installed is different from 6.1 accidents. The data suggest that the population mean is not significantly different from 5.8 at αα = 0.01, so there is statistically insignificant evidence to conclude that the population mean number of accidents per year at intersections with cameras installed is different from 5.8 accidents. The data suggest that the populaton mean is significantly different from 5.8 at αα = 0.01, so there is statistically significant evidence to conclude that the population mean number of accidents per year at intersections with cameras installed is different from 5.8 accidents. Interpret the p-value in the context of the study. There is a 1.81758026% chance that the population mean number of accidents per year at intersections with cameras installed is not equal to 5.8. If the population mean number of accidents per year at intersections with cameras installed is 5.8 and if another 46 intersections with cameras installed are observed then there would be a 1.81758026% chance that the sample mean for these 46 intersections with cameras installed would either be less than 6 or greater than 6.1. There is a 1.81758026% chance of a Type I error. If the population mean number of accidents per year at intersections with cameras installed is 5.8 and if another 46 intersections with cameras installed are observed then there would be a 1.81758026% chance that the population mean would either be less than 6 or greater than 6.1. Interpret the level of significance in the context of the study. There is a 1% chance that the population mean number of accidents per year at intersections with cameras installed is different from 5.8. If the population population mean number of accidents per year at intersections with cameras installed is different from 5.8 and if another 46 intersections with cameras installed are observed then there would be a 1% chance that we would end up falsely concluding that the population mean number of accidents per year at intersections with cameras installed is equal to 5.8. There is a 1% chance that you will get in a car accident, so please wear a seat belt. If the population mean number of accidents per year at intersections with cameras installed is 5.8 and if another 46 intersections with cameras installed are observed then there would be a 1% chance that we would end up falsely concluding that the population mean number of accidents per year at intersections with cameras installed is different from 5.8.

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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Question

The p-value = (Please show your answer to 4 decimal places.)
The p-value is ? α
Based on this, we should the null hypothesis.
Thus, the final conclusion is that ...
- The data suggest that the sample mean is not significantly different from 5.8 at αα = 0.01, so there is statistically insignificant evidence to conclude that the sample mean number of accidents per year at intersections with cameras installed is different from 6.1 accidents.
- The data suggest that the population mean is not significantly different from 5.8 at αα = 0.01, so there is statistically insignificant evidence to conclude that the population mean number of accidents per year at intersections with cameras installed is different from 5.8 accidents.
- The data suggest that the populaton mean is significantly different from 5.8 at αα = 0.01, so there is statistically significant evidence to conclude that the population mean number of accidents per year at intersections with cameras installed is different from 5.8 accidents.
Interpret the p-value in the context of the study.
- There is a 1.81758026% chance that the population mean number of accidents per year at intersections with cameras installed is not equal to 5.8.
- If the population mean number of accidents per year at intersections with cameras installed is 5.8 and if another 46 intersections with cameras installed are observed then there would be a 1.81758026% chance that the sample mean for these 46 intersections with cameras installed would either be less than 6 or greater than 6.1.
- There is a 1.81758026% chance of a Type I error.
- If the population mean number of accidents per year at intersections with cameras installed is 5.8 and if another 46 intersections with cameras installed are observed then there would be a 1.81758026% chance that the population mean would either be less than 6 or greater than 6.1.
Interpret the level of significance in the context of the study.
- There is a 1% chance that the population mean number of accidents per year at intersections with cameras installed is different from 5.8.
- If the population population mean number of accidents per year at intersections with cameras installed is different from 5.8 and if another 46 intersections with cameras installed are observed then there would be a 1% chance that we would end up falsely concluding that the population mean number of accidents per year at intersections with cameras installed is equal to 5.8.
- There is a 1% chance that you will get in a car accident, so please wear a seat belt.
- If the population mean number of accidents per year at intersections with cameras installed is 5.8 and if another 46 intersections with cameras installed are observed then there would be a 1% chance that we would end up falsely concluding that the population mean number of accidents per year at intersections with cameras installed is different from 5.8.

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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