Module #9 - T-Test for Indpendent Samples

This week's topics covered running an independent samples t-test and interpreting using R.

### Question # 1 : Find your two sample means.

```  > x <- c(9,8,3,8,10)
> y <- c(3,1,2,6,4,3,6)
> tTest <- t.test(x,y)
> tTest\$estimate
mean of x mean of y
7.600000  3.571429
```

### Question # 2 : Find the degrees of freedom(s).

```  > tTest\$parameter
df
6.768656
```

### Question # 3 : Find t-test statistic score (s).

```  > tTest\$statistic
t
2.865148
```

### Question # 4 : Find the P value(s).

```  > tTest\$p.value
 0.02505219
```

### Question # 5 : Assume you had chosen an alpha value of .05., Would this result have been statistically significant?

```  Yes. The p-value is <= 0.05.
```

### Question # 6 : What critical value would your obtained t-test value have to exceed to be significant at the .01 level (assume a two-tailed test)?

```  > z <- qnorm(0.99 + (0.01 / 2))
> p <- pnorm(z)
> z
 2.575829
> p
 0.995
For the t-test to exceed the significance
value of 0.01, z must be 2.576 or p must
be 0.995
```