Answer:
Step-by-step explanation:
Hello!
The variable of study is
X: number of complaints per industry (Categorized: Bank, Cable, Car, Cell, Collection
Considering this is a categorical variable, and the hypothesis is that all categories have the same probability, you have to apply a Chi-Square Goodness to Fit test.
Observed frequencies per category
1) Bank: 26
2) Cable: 44
3) Car: 42
4) Cell: 60
5) Collection: 28
Total= 200
Statistical hypotheses:
H₀: P₁=P₂=P₃=P₄=P₅=1/5
H₁: At least one of the proposed proportions is different.
α: 0.01

For this test the formula for the expected frequencies is:

So the expected values for each category is:






This test is one tailed and so is its p-value, under a Chi-square with 4 degrees of freedom p-value: 0.021484.
The p-value is less than the significance level so the decision is to reject the null hypothesis.
c. The industry with most complaints is the cellular phone providers
I hope this helps!
1 km 125m = 1125 meter on Monday
1125-375=750 meter on Tuesday
Convert each to decimal form
that will be 0.122... , 0.1225, 0.12 and 0.056
so from greatest to least that is 0.1225 , 0.1222...., 0.12, 0.056
that is 0.1225 , 012(with bar over the 2) , 3/25 , 7/125
Answer:
Step-by-step explanation:
x=6
9514 1404 393
Answer:
110%
Step-by-step explanation:
The whole left square is shaded, so that is 100%.
The right square is divided into 10 equal parts, so each one is 100%/10 = 10% of the whole. One of those is shaded.
The whole amount shaded is ...
100% + 10% = 110%