The table depicts a two-way ANOVA in which gender has two groups (male and female), marital status has three groups (married, single never married, divorced), and the means refer to happiness scores

Need a few examples of a null hypothesis that would use a t test statistical analysis.. And then use the same hypothetical situation taken in the t test hypothesis, and turn it into a null hypothesis using a one-way ANOVA analysis and a two-way ANOVA. 

Next; 
The table depicts a two-way ANOVA in which gender has two groups (male and female), marital status has three groups (married, single never married, divorced), and the means refer to happiness scores (n = 100): 

a. What is/are the independent variable(s)? What is/are the dependent variable(s)?
b. What would be an appropriate null hypothesis? Alternate hypothesis?
c. What are the degrees of freedom for 1) gender, 2) marital status, 3) interaction between gender and marital status, and 4) error or within variance?
d. Calculate the mean square for 1) gender, 2) marital status, 3) interaction between gender and marital status, and 4) error or within variance.
e. Calculate the F ratio for 1) gender, 2) marital status, and 3) interaction between gender and marital status.
f. Identify the critical Fs at alpha = .05 for 1) gender, 2) marital status, and 3) interaction between gender and marital status.
g. If alpha is set at .05, what conclusions can you make?

I need to put it in a graph like this: 

Source Sum of Squares (degrees of freedom [df]) Mean Square Fobt.Fcrit.
Gender 68.15 ? ? ? ?
Marital Status 127.37 ? ? ? ?
Gender * Marital
Status (A x B) 41.90 ? ? ? ?
Error (Within) 864.82 ? ? NA NA

Total 1102.24 99 NA NA NA

***You are asked to calculate the F value and compare it to the critical F value to determine whether the test is significant or not. 


And lastly; the largest part:
A study wants to examine the relationship between student anxiety for an exam and the number of hours studied. The data is as follows: 


Student Anxiety Scores
5
10
5
11
12
4
3
2
6
1


Study Hours 
1
6
2
8
5
1
4
6
5
2


1.Why is a correlation the most appropriate statistic?
2.What is the null and alternate hypothesis? 
3.What is the correlation between student anxiety scores and number of study hours? Select alpha and interpret your findings. Make sure to note whether it is significant or not and what the effect size is. 
4.How would you interpret this?
5.What is the probability of a type I error? What does this mean?
6.How would you use this same information but set it up in a way that allows you to conduct a t-test? An ANOVA?