consider the following haypothesis
Ho: =20
Ha: =20
It is impossible to determine what the hypothesis is referring to based on the given information "=20". More contextual information is needed to understand the hypothesis.
The following data are from simple random sample 5,8,10,14
A, what is the point estimate of the population mean
B, what is the point estimate of the population standard devition
A) The point estimate of the population mean is calculated by taking the average of the sample.
Point estimate of population mean = (5 + 8 + 10 + 14) / 4 = 37 / 4 = 9.25
B) The point estimate of the population standard deviation is calculated using the sample standard deviation formula.
First, calculate the sample mean:
Sample mean = (5 + 8 + 10 + 14) / 4 = 37 / 4 = 9.25
Next, calculate the sample variance:
Sample variance = ((5-9.25)^2 + (8-9.25)^2 + (10-9.25)^2 + (14-9.25)^2) / (4-1)
= (18.5625 + 1.0625 + 0.0625 + 20.0625) / 3
= 40.75 / 3
= 13.5833
Finally, calculate the sample standard deviation:
Sample standard deviation = √(Sample variance) = √(13.5833) ≈ 3.68
Simple random sample of 50items from apopulationwhith=6resultedinsamplemean32
A,providea90 confidence interval for the population mean
B,providea95 confidence interval for the population mean
C,providea95 confidence interval for the populationmean
To calculate the confidence intervals for the population mean, we need to know the sample standard deviation. Unfortunately, this information is missing from the given data. Without the sample standard deviation, we cannot calculate the confidence intervals.
The null hypothesis (Ho) and alternative hypothesis (Ha) you provided are not formulated correctly. In a hypothesis test, the null hypothesis represents a statement of equality or no difference, while the alternative hypothesis represents a statement of inequality or difference.
To correctly formulate the null and alternative hypotheses, you need to specify the variables or parameters you are testing and the direction of the inequality. Here is an example of how you could formulate the hypotheses based on your question:
Ho: µ = 20 (The population mean is equal to 20)
Ha: µ ≠ 20 (The population mean is not equal to 20)
In this case, µ represents the population mean. The null hypothesis states that the population mean is equal to 20, while the alternative hypothesis states that the population mean is not equal to 20.
It seems that there is some confusion regarding the hypothesis statement you provided. The hypothesis statement should usually involve a claim about a population parameter, rather than assigning a value to it.
In a standard hypothesis test, we have a null hypothesis (Ho) and an alternative hypothesis (Ha) which represents the claim we are testing. The null hypothesis typically assumes no effect, no difference, or no relationship, while the alternative hypothesis suggests otherwise.
In your case, the hypothesis statements you provided do not have any claim related to a population parameter. It appears that you have assigned a specific value of 20 to both the null and alternative hypotheses. However, without any context or additional information, it is difficult to determine what exactly you are trying to test or hypothesize.
To create a proper hypothesis statement, you need to specify a population parameter and make a claim about it. For example:
Ho: The mean age of a certain population is equal to 20.
Ha: The mean age of a certain population is not equal to 20.
In this case, we are testing if the average age of a specific population is equal to 20 or not.