You the researcher want to test the hypotheses that people with college degrees (BA) are more likely to support a government-spo
nsored national health care plan than are people with PhD's. Based on the data in the table below, you will evaluate this hypothesis and interpret the results. Person Highest Degree Support for a National Health Type of
Care Plan Insurance
1 BA High Public
2 PhD Low Public
3 PhD High Private
4 PhD Low Public
5 BA Low Public
6 PhD Low Private
7 BA Low Private
8 BA Low Public
9 PhD High Public
10 BA High Private
Care Plan Insurance
1 BA High Public
2 PhD Low Public
3 PhD High Private
4 PhD Low Public
5 BA Low Public
6 PhD Low Private
7 BA Low Private
8 BA Low Public
9 PhD High Public
10 BA High Private
1 answer:
Answer:
hello your question is incomplete attached below is the missing part
Highest Degree : Ordinal Data
Support for a National Health plan- Ordinal Data
Types of insurance - Categorical data
Step-by-step explanation:
After the evaluation of the given results The types of variables associated with the results are :
For Highest Degree the variable is an Ordinal Data because there is a particular order used for writing/recording the highest degree
Support for a National Health plan- Ordinal Data Because there is also a particular order for the support for
Types of insurance - Categorical data no particular order followed
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Answer:
0% probability that the sample mean would have been as high or higher than 3.1 if the company’s claims were true.
Step-by-step explanation:
To solve this question, we need to understand the normal probability distribution and the central limit theorem.
Normal probability distribution
Problems of normally distributed samples are solved using the z-score formula.
In a set with mean and standard deviation
, the zscore of a measure X is given by:
The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.
Central limit theorem
The Central Limit Theorem estabilishes that, for a random variable X, with mean and standard deviation
, a large sample size can be approximated to a normal distribution with mean
and standard deviation
In this problem, we have that:
What is the approximate probability that the sample mean would have been as high or higher than 3.1 if the company’s claims were true?
This is 1 subtracted by the pvalue of Z when X = 3.1. So
By the Central Limit Theorem
has a pvalue of 1.
1 - 1 = 0
0% probability that the sample mean would have been as high or higher than 3.1 if the company’s claims were true.
