Samantha has three times as many basketball cards as Mark Mark has 12 caught baseball cards right in equation that shows how man
y Samantha cards has
2 answers:
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9514 1404 393
Answer:
CPCTC
Step-by-step explanation:
The applicable reason for statement 4 is "Corresponding Parts of Congruent Triangles are Congruent (CPCTC)".
The reason shown in your problem statement is applicable only within one triangle. The segments of interest are in two different triangles.
Answer:
And we can find the p value using the following excel code:
"=1-CHISQ.DIST(13.833,4,TRUE)"
Since the p value is lower than the significance level we can reject the null hypothesis at 5% of significance, and we can conclude that the drowsiness are NOT equally distributed among office workers .
Step-by-step explanation:
Previous concepts
A chi-square goodness of fit test "determines if a sample data matches a population".
A chi-square test for independence "compares two variables in a contingency table to see if they are related. In a more general sense, it tests to see whether distributions of categorical variables differ from each another".
Assume the following dataset:
Method Beverage Nap Walk Snack Other
Number 21 16 10 8 5
The total on this case is 60
We need to conduct a chi square test in order to check the following hypothesis:
H0: Drowsiness are equally distributed among office workers
H1: Drowsiness IS NOT equally distributed among office workers
The level of significance assumed for this case is
The statistic to check the hypothesis is given by:
The table given represent the observed values, we just need to calculate the expected values with the following formula
And the calculations are given by:
And the expected values are given by:
Method Beverage Nap Walk Snack Other
Number 12 12 12 12 12
And now we can calculate the statistic:
Now we can calculate the degrees of freedom for the statistic given by:
And we can calculate the p value given by:
And we can find the p value using the following excel code:
"=1-CHISQ.DIST(13.833,4,TRUE)"
Since the p value is lower than the significance level we can reject the null hypothesis at 5% of significance, and we can conclude that the drowsiness are NOT equally distributed among office workers .