To test whether the distribution of sample outcomes match a hypothesized distribution, the appropriate test is (a) one-factor anova (b) two- factor anova (c) goodness –of fit

(c) goodness of fit

Step-by-step explanation:

Chi-square Goodness of fit is used to test how the observed value of the given event differs significantly the expected value. It means that goodness of fit is used to examine the observed sample value to the expected probability distribution.

The Chi-Square Goodness of fit is used as:

Firstly, we set up hypothesis as:

Null Hypothesis (H₀) : There is no difference between the observed value and expected value.

Alternative Hypothesis (H₁) : There is difference between the observed value and expected value.

Then we use the formula as :

where, E is expected value

and O is observed value.

The one-factor ANOVA is use to compare the mean of two or more variables.

The two-factor ANOVA is use to compare the mean difference of groups.

13

step-by-step explanation:

169-1=168

168-3=165

165-5=160

160-7=153

153-9=144

144-11=133

133-13=120

120-15=105

105-17=88

88-19=69

69-21=48

48-23=25

25-25=0

since it took 13times to completely subtract it hence its square root is 13