Question

# R Hypothesis Tests

install.packages("dplyr")

tScore_before <- c(40, 62, 74, 22, 64, 65, 49, 49, 49)

tScore_after <- c(68, 61, 64, 76, 90, 75, 66, 60, 63)

# Create a data frame

my_data <- data.frame(

                group = rep(c("Score Before", "Score After"), each = 9),

                scores = c(tScore_before, tScore_after)

                )

# Print all data

print(my_data)

#Compute summary statistics by groups

library(dplyr)

group_by(my_data, group) %>%

summarise(

    count = n(),

    mean = mean(scores, na.rm = TRUE),

    sd = sd(scores, na.rm = TRUE)

)

# Compute Unpaired Two Sample t-test

res <- t.test(tScore_before, tScore_after, var.equal = TRUE)

res

# Compute independent t-test

res <- t.test(scores ~ group, data = my_data, var.equal = TRUE)

res

#test whether the average score before score is less than the average after score, type this:

t.test(scores ~ group, data = my_data,

        var.equal = TRUE, alternative = "less")

The instructions say to include a snippet of the graph created but I do not get a graph after running this code. Just wanted to make sure there is not one.

Answer 1

*************OUTPUT after RUNNING CODE IN R**************

> # R Hypothesis Tests
>
> #install.packages("dplyr")
>
>
> tScore_before <- c(40, 62, 74, 22, 64, 65, 49, 49, 49)
>
> tScore_after <- c(68, 61, 64, 76, 90, 75, 66, 60, 63)
>
> # Create a data frame
>
> my_data <- data.frame(
+   
+ group = rep(c("Score Before", "Score After"), each = 9),
+   
+ scores = c(tScore_before, tScore_after)
+   
+ )
>
>
> # Print all data
>
> print(my_data)
group scores
1 Score Before 40
2 Score Before 62
3 Score Before 74
4 Score Before 22
5 Score Before 64
6 Score Before 65
7 Score Before 49
8 Score Before 49
9 Score Before 49
10 Score After 68
11 Score After 61
12 Score After 64
13 Score After 76
14 Score After 90
15 Score After 75
16 Score After 66
17 Score After 60
18 Score After 63
>
>
> #Compute summary statistics by groups
>
> library(dplyr)
>
> group_by(my_data, group) %>%
+   
+ summarise(
+   
+ count = n(),
+   
+ mean = mean(scores, na.rm = TRUE),
+   
+ sd = sd(scores, na.rm = TRUE)
+   
+ )
# A tibble: 2 x 4
group count mean sd
<fct> <int> <dbl> <dbl>
1 Score After 9 69.2 9.63
2 Score Before 9 52.7 15.7
>
>
> # Compute Unpaired Two Sample t-test
>
> res <- t.test(tScore_before, tScore_after, var.equal = TRUE)
>
> res

   Two Sample t-test

data: tScore_before and tScore_after
t = -2.7007, df = 16, p-value = 0.01575
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
-29.550620 -3.560491
sample estimates:
mean of x mean of y
52.66667 69.22222

>
>
> # Compute independent t-test
>
> res <- t.test(scores ~ group, data = my_data, var.equal = TRUE)
>
> res

   Two Sample t-test

data: scores by group
t = 2.7007, df = 16, p-value = 0.01575
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
3.560491 29.550620
sample estimates:
mean in group Score After mean in group Score Before
69.22222 52.66667

>
>
> #test whether the average score before score is less than the average after score, type this:
>
> t.test(scores ~ group, data = my_data,
+
+ var.equal = TRUE, alternative = "less")

   Two Sample t-test

data: scores by group
t = 2.7007, df = 16, p-value = 0.9921
alternative hypothesis: true difference in means is less than 0
95 percent confidence interval:
-Inf 27.25786
sample estimates:
mean in group Score After mean in group Score Before
69.22222 52.66667

*********************************************************************

No commmand in code create graph.so these code doesn't have graph.