calculate independent sample t test for an equal variance with the following data set.
CLOCKWISE(X)
185
182
184.3
176
179.5
178.2
181.7
159.5
162.3
160.5
166
163.5
162.7
167
167
163
162.5
162
163
161
163.5
160.3
167.3
127.8
128.8
137
113.2
116.5
131.5
144.5
143.3
152
143
141.2
141
142.6
141.7
126.6
128
140
NA
NA
141.6
142
138
140
138.4
142
137.8
140.4
137.4
134.2
COUNTER-CLOCKWISE(Y)
136.8
138.8
139
138.8
136.8
152.2
152.4
153.2
152.8
151.6
149.6
152.8
152.6
149.2
150.6
150
148.6
149.4
149.6
149.6
151
149.2
148.2
152.2
150.2
150.8
149.4
148.2
150.2
148.6
149
150.2
148.6
150.8
149
149.8
146.6
150.2
148.4
149.2
149.2
148.8
150.2
148.4
148.4
149.6
148.8
147.2
148.8
154
150.4
148
144
149.2
148.2
149
149.6
146.8
148.6
149.8
149
148.2
147.8
147.2
147
149.8
148.2
146.4
146
147.2
148.1
146.1
150
146.8
152
149
148.8
149.2
147.9
151.2
146.6
149.7
148.3
147.5
148.7
147.9
148.7
149.7
147.5
151.6
150.9
150.4
150.7
148.5
146.7
1 answer
Performing a Levene's Test for Equal Variances:
Null Hypothesis (H0): The variances of the two groups are equal.
Alternative Hypothesis (Ha): The variances of the two groups are not equal.
Let's start by conducting the Levene's test using the clockwisepackage in R:
```R
# Step 1: Enter the data
CLOCKWISE <- c(185, 182, 184.3, 176, 179.5, 178.2, 181.7, 159.5, 162.3, 160.5, 166, 163.5, 162.7, 167, 167, 163, 162.5, 162, 163, 161, 163.5, 160.3, 167.3, 127.8, 128.8, 137, 113.2, 116.5, 131.5, 144.5, 143.3, 152, 143, 141.2, 141, 142.6, 141.7, 126.6, 128, 140, NA, NA, 141.6, 142, 138, 140, 138.4, 142, 137.8, 140.4, 137.4, 134.2)
COUNTER_CLOCKWISE <- c(136.8, 138.8, 139, 138.8, 136.8, 152.2, 152.4, 153.2, 152.8, 151.6, 149.6, 152.8, 152.6, 149.2, 150.6, 150, 148.6, 149.4, 149.6, 149.6, 151, 149.2, 148.2, 152.2, 150.2, 150.8, 149.4, 148.2, 150.2, 148.6, 149, 150.2, 148.6, 150.8, 149, 149.8, 146.6, 150.2, 148.4, 149.2, 149.2, 148.8, 150.2, 148.4, 148.4, 149.6, 148.8, 147.2, 148.8, 154, 150.4, 148, 144, 149.2, 148.2, 149, 149.6, 146.8, 148.6, 149.8, 149, 148.2, 147.8, 147.2, 147, 149.8, 148.2, 146.4, 146, 147.2, 148.1, 146.1, 150, 146.8, 152, 149, 148.8, 149.2, 147.9, 151.2, 146.6, 149.7, 148.3, 147.5, 148.7, 147.9, 148.7, 149.7, 147.5, 151.6, 150.9, 150.4, 150.7, 148.5, 146.7)
# Step 2: Install the clockwise package (if not already installed)
install.packages("clockwise")
# Step 3: Load the clockwisepackage
library(clockwise)
# Step 4: Perform Levene's test
levene.test(CLOCKWISE, COUNTER_CLOCKWISE)
```
The output of the Levene's test will provide a p-value. If the p-value is greater than the significance level (usually 0.05), we fail to reject the null hypothesis and conclude that the variances of the two groups are equal. If the p-value is less than 0.05, we reject the null hypothesis and conclude that the variances are not equal.
Once we determine if the variances are equal or not, we can proceed with the independent sample t-test.
Please note that there are some missing values (NA) in the CLOCKWISE group. To run the t-test, we will need to handle these missing values by either excluding them or using an appropriate imputation method.