How would I solve this assuming the population variances are equal? Plants convert carbon dioxide (CO2) in the atmo-sphere, along with water and energy from sunlight, intothe energy they need for growth and reproduction.Experiments were performed under normal atmosphericair conditions and in air with enriched CO2 concentra-tions to determine the effect on plant growth. The plantswere given the same amount of water and light for a four-week period. The following table gives the plant growthsin grams:Normal Air 4.67 4.21 2.18 3.91 4.09 5.24 2.94 4.714.04 5.79 3.80 4.38Enriched Air 5.04 4.52 6.18 7.01 4.36 1.81 6.22 5.70On the basis of these data, determine whether CO2-enriched atmosphere increases plant growth.

H0 is accepted.the average growth of plant is same in both normal and enriched air.Explanation:Step…

Answered: Plants convert carbon dioxide (CO2) in…

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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A2
In a hypothesis test, the null hypothesis states that the population variance is equal to 25. A sample of size 36 is taken and the sample variance is found to be 30. What is the test statistic for this hypothesis test?
Earlier this semester, we learned to use 2-Sample-TTest to compare the population means of two independent populations. One-way ANOVA is more powerful because it could compare the population means of three or more independent populations. However, use of one-way ANOVA also requires the assumption that the populations have the same variance. In this exercise, we will compare and contrast One-way ANOVA and 2-Sample-TTest. With the 2-Sample- TTEST, we will first choose 'No' for the pooled variances option, then re-run the test while choosing 'Yes' for the pooled variances option. Use the following data to complete these tasks. Depending on if you choose to do this by hand or using code, use the data format that suits you best - LONG form on top or WIDE form on bottom. Treatment One One One One One One One One Two Two Two Two Two Two Two Two Treatment Treatment One Two 5.6 4.7 3.6 3.9 5.2 4.3 4.1 4.8 Response 5.6 4.7 3.6 3.9 5.2 4.3 4.1 4.8 3.4 2.3 4.4 3.5 3.7 5.8 2.8 4.7 p-value= 3.4 2.3…
How did you get the variance for this problem ?
Construct a numerical example, i.e., a data set, such that a two-sample t-test will yield an insignificant test result but a pair t-test will yield a significant test result. (For the two-sample t-test, you can either assume equal variances or unequal variances, which will not affect the key idea of this question.) I need to know how this is possible and what the basics of making this data set should be.
Earlier this semester, we learned to use 2-Sample-TTest to compare the population means of two independent populations. One-way ANOVA is more powerful because it could compare the population means of three or more independent populations. However, use of one-way ANOVA also requires the assumption that the populations have the same variance. In this exercise, we will compare and contrast One-way ANOVA and 2-Sample-TTest. With the 2-Sample- TTEST, we will first choose 'No' for the pooled variances option, then re-run the test while choosing 'Yes' for the pooled variances option. Use the following data to complete these tasks. Depending on if you choose to do this by hand or using code, use the data format that suits you best - LONG form on top or WIDE form on bottom. Treatment One One One One One One One Two Two Two Two Two Two Two Treatment One 7.1 8.5 7.6 7.7 6.9 8.5 7.8 Response 7.1 8.5 7.6 7.7 6.9 8.5 7.8 1.4 4.1 4.3 3.9 4 4 4.6 p-value= Treatment Two 1.4 4.1 4.3 3.9 4 4 4.6 1. Use…
How do I get the variance ?
suppose that we have disjoint normal populations A and B and we want to find the standard error estimate for estimating the difference in their means. We have an IRS from A of size 8 with variance 25 and an IRS from B of size 9 with variance 16. What is the resulting standard error estimate if we assume both populations have the same population variance?

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