Imagine that you have entered the following distribution of scores into the program: 7, 9, 6, 3, 7, 8, 4, 10, 7, 9. The mean of
1 answer:
Answer:
3
Step-by-step explanation:
Mean refers to the average value of the set of data.
It is the central value of the set of data.
Another word for Mean is average.
Given scores:7, 9, 6, 3, 7, 8, 4, 10, 7, 9
Solution:
Sum of observations =
Number of observations = 10
Mean = Sum of observations/Number of observations =
If observation 3 is removed:
Sum of observations =
Number of observations = 9
Mean = Sum of observations/Number of observations =
If observation 4 is removed:
Sum of observations =
Number of observations = 9
Mean =
If observation 6 is removed:
Sum of observations =
Number of observations = 9
Mean =
If observation 7 is removed:
Sum of observations =
Number of observations = 7
Mean =
If observation 8 is removed:
Sum of observations =
Number of observations = 9
Mean =
If observation 9 is removed:
Sum of observations =
Number of observations = 8
Mean =
If observation 10 is removed:
Sum of observations =
Number of observations = 9
Mean =
Therefore, mean of this distribution of scores would be changed the most if a score 3 was removed from the data set.
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Answer:
a) We need to conduct a hypothesis in order to test the claim that the true proportion p is greatr than 0.3, so then the system of hypothesis are.:
Null hypothesis:
Alternative hypothesis:
Right tailed test
b)
c) So the p value obtained was a very low value and using the significance level given we have
so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 1% of significance the proportion of interest is higher than 0.3
Step-by-step explanation:
Part a: Concepts and formulas to use
We need to conduct a hypothesis in order to test the claim that the true proportion p is greatr than 0.3, so then the system of hypothesis are.:
Null hypothesis:
Alternative hypothesis:
Right tailed test
When we conduct a proportion test we need to use the z statisitc, and the is given by:
(1)
The One-Sample Proportion Test is used to assess whether a population proportion is significantly different from a hypothesized value
.
Calculate the statistic
For this case the statistic is given by
Part b: Statistical decision
It's important to refresh the p value method or p value approach . "This method is about determining "likely" or "unlikely" by determining the probability assuming the null hypothesis were true of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed". Or in other words is just a method to have an statistical decision to fail to reject or reject the null hypothesis.
The next step would be calculate the p value for this test.
Since is a right tailed test the p value would be:
Part c
So the p value obtained was a very low value and using the significance level given we have
so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 1% of significance the proportion of interest is higher than 0.3