Women are recommended to consume 1720 calories per day. You suspect that the average calorie intake is different for women at your college. The data for the 12 women who participated in the study is shown below: 1837, 1618, 1820, 1846, 1640, 1700, 1655, 1473, 1563, 1840, 1796, 1854 Assuming that the distribution is normal, what can be concluded at the αα = 0.10 level of significance? For this study, we should use Select an answer z-test for a population proportion t-test for a population mean The null and alternative hypotheses would be: H0:H0: ? μ p Select an answer > < ≠ = H1:H1: ? p μ Select an answer ≠ = < > The test statistic ? t z = (please show your answer to 3 decimal places.) The p-value = (Please show your answer to 4 decimal places.) The p-value is ? > ≤ αα Based on this, we should Select an answer reject accept fail to reject the null hypothesis. Thus, the final conclusion is that ... The data suggest that the population mean calorie intake for women at your college is not significantly different from 1720 at αα = 0.10, so there is insufficient evidence to conclude that the population mean calorie intake for women at your college is different from 1720. The data suggest the population mean is not significantly different from 1720 at αα = 0.10, so there is sufficient evidence to conclude that the population mean calorie intake for women at your college is equal to 1720. The data suggest the populaton mean is significantly different from 1720 at αα = 0.10, so there is sufficient evidence to conclude that the population mean calorie intake for women at your college is different from 1720. Interpret the p-value in the context of the study. If the population mean calorie intake for women at your college is 1720 and if you survey another 12 women at your college then there would be a 99.6525554% chance that the population mean would either be less than 1720 or greater than 1720. There is a 99.6525554% chance of a Type I error. If the population mean calorie intake for women at your college is 1720 and if you survey another 12 women at your college, then there would be a 99.6525554% chance that the sample mean for these 12 women would either be less than 1720 or greater than 1720. There is a 99.6525554% chance that the population mean calorie intake for women at your college is not equal to 1720. Interpret the level of significance in the context of the study. If the population mean calorie intake for women at your college is 1720 and if you survey another 12 women at your college, then there would be a 10% chance that we would end up falsely concuding that the population mean calorie intake for women at your college is different from 1720. There is a 10% chance that the population mean calorie intake for women at your college is different from 1720. There is a 10% chance that the women at your college are just eating too many desserts and will all gain the freshmen 15. If the population mean calorie intake for women at your college is different from 1720 and if you survey another 12 women at your college, then there would be a 10% chance that we would end up falsely concuding that the population mean calorie intake for women at your college is equal to 1720.

Women are recommended to consume 1720 calories per day. You suspect that the average calorie intake is different for women at your college. The data for the 12 women who participated in the study is shown below: 1837, 1618, 1820, 1846, 1640, 1700, 1655, 1473, 1563, 1840, 1796, 1854 Assuming that the distribution is normal, what can be concluded at the αα = 0.10 level of significance? For this study, we should use Select an answer z-test for a population proportion t-test for a population mean The null and alternative hypotheses would be: H0:H0: ? μ p Select an answer > < ≠ = H1:H1: ? p μ Select an answer ≠ = < > The test statistic ? t z = (please show your answer to 3 decimal places.) The p-value = (Please show your answer to 4 decimal places.) The p-value is ? > ≤ αα Based on this, we should Select an answer reject accept fail to reject the null hypothesis. Thus, the final conclusion is that ... The data suggest that the population mean calorie intake for women at your college is not significantly different from 1720 at αα = 0.10, so there is insufficient evidence to conclude that the population mean calorie intake for women at your college is different from 1720. The data suggest the population mean is not significantly different from 1720 at αα = 0.10, so there is sufficient evidence to conclude that the population mean calorie intake for women at your college is equal to 1720. The data suggest the populaton mean is significantly different from 1720 at αα = 0.10, so there is sufficient evidence to conclude that the population mean calorie intake for women at your college is different from 1720. Interpret the p-value in the context of the study. If the population mean calorie intake for women at your college is 1720 and if you survey another 12 women at your college then there would be a 99.6525554% chance that the population mean would either be less than 1720 or greater than 1720. There is a 99.6525554% chance of a Type I error. If the population mean calorie intake for women at your college is 1720 and if you survey another 12 women at your college, then there would be a 99.6525554% chance that the sample mean for these 12 women would either be less than 1720 or greater than 1720. There is a 99.6525554% chance that the population mean calorie intake for women at your college is not equal to 1720. Interpret the level of significance in the context of the study. If the population mean calorie intake for women at your college is 1720 and if you survey another 12 women at your college, then there would be a 10% chance that we would end up falsely concuding that the population mean calorie intake for women at your college is different from 1720. There is a 10% chance that the population mean calorie intake for women at your college is different from 1720. There is a 10% chance that the women at your college are just eating too many desserts and will all gain the freshmen 15. If the population mean calorie intake for women at your college is different from 1720 and if you survey another 12 women at your college, then there would be a 10% chance that we would end up falsely concuding that the population mean calorie intake for women at your college is equal to 1720.

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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1837, 1618, 1820, 1846, 1640, 1700, 1655, 1473, 1563, 1840, 1796, 1854

Assuming that the distribution is normal, what can be concluded at the αα = 0.10 level of significance?

For this study, we should use Select an answer z-test for a population proportion t-test for a population mean
The null and alternative hypotheses would be:

H0:H0: ? μ p Select an answer > < ≠ =

H1:H1: ? p μ Select an answer ≠ = < >

The test statistic ? t z = (please show your answer to 3 decimal places.)
The p-value = (Please show your answer to 4 decimal places.)
The p-value is ? > ≤ αα
Based on this, we should Select an answer reject accept fail to reject the null hypothesis.
Thus, the final conclusion is that ...
- The data suggest that the population mean calorie intake for women at your college is not significantly different from 1720 at αα = 0.10, so there is insufficient evidence to conclude that the population mean calorie intake for women at your college is different from 1720.
- The data suggest the population mean is not significantly different from 1720 at αα = 0.10, so there is sufficient evidence to conclude that the population mean calorie intake for women at your college is equal to 1720.
- The data suggest the populaton mean is significantly different from 1720 at αα = 0.10, so there is sufficient evidence to conclude that the population mean calorie intake for women at your college is different from 1720.
Interpret the p-value in the context of the study.
- If the population mean calorie intake for women at your college is 1720 and if you survey another 12 women at your college then there would be a 99.6525554% chance that the population mean would either be less than 1720 or greater than 1720.
- There is a 99.6525554% chance of a Type I error.
- If the population mean calorie intake for women at your college is 1720 and if you survey another 12 women at your college, then there would be a 99.6525554% chance that the sample mean for these 12 women would either be less than 1720 or greater than 1720.
- There is a 99.6525554% chance that the population mean calorie intake for women at your college is not equal to 1720.
Interpret the level of significance in the context of the study.
- If the population mean calorie intake for women at your college is 1720 and if you survey another 12 women at your college, then there would be a 10% chance that we would end up falsely concuding that the population mean calorie intake for women at your college is different from 1720.
- There is a 10% chance that the population mean calorie intake for women at your college is different from 1720.
- There is a 10% chance that the women at your college are just eating too many desserts and will all gain the freshmen 15.
- If the population mean calorie intake for women at your college is different from 1720 and if you survey another 12 women at your college, then there would be a 10% chance that we would end up falsely concuding that the population mean calorie intake for women at your college is equal to 1720.

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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