data01 %>%
group_by(PreferredOLM) %>%
dplyr::summarise(N=length(AD), Mean=mean(AD), SD=sd(AD))
## # A tibble: 2 x 4
## PreferredOLM N Mean SD
## <chr> <int> <dbl> <dbl>
## 1 Asynchronous 39 3.34 0.660
## 2 Synchronous 20 3.69 0.657
t.test(AD~PreferredOLM, data01, var.equal = FALSE)
##
## Welch Two Sample t-test
##
## data: AD by PreferredOLM
## t = -1.9012, df = 38.549, p-value = 0.06478
## alternative hypothesis: true difference in means between group Asynchronous and group Synchronous is not equal to 0
## 95 percent confidence interval:
## -0.71045836 0.02213927
## sample estimates:
## mean in group Asynchronous mean in group Synchronous
## 3.344729 3.688889
boxplot(AD~PreferredOLM,data01)
normality(data01$AD, data01$PreferredOLM, data01)
## T statistic of Raw Data: -1.899007
## T statistic of Rank Data: -1.728871
## Difference: 0.170136
##
## Decision: Assume that the variables are normally distirubted and use T-test. Check the number of observations per group
data01 %>%
group_by(PreferredOLM) %>%
dplyr::summarise(N=length(BD), Mean=mean(BD), SD=sd(BD))
## # A tibble: 2 x 4
## PreferredOLM N Mean SD
## <chr> <int> <dbl> <dbl>
## 1 Asynchronous 39 3.52 0.394
## 2 Synchronous 20 3.62 0.375
t.test(BD~PreferredOLM, data01, var.equal = FALSE)
##
## Welch Two Sample t-test
##
## data: BD by PreferredOLM
## t = -0.90729, df = 40.14, p-value = 0.3697
## alternative hypothesis: true difference in means between group Asynchronous and group Synchronous is not equal to 0
## 95 percent confidence interval:
## -0.3075652 0.1169669
## sample estimates:
## mean in group Asynchronous mean in group Synchronous
## 3.521368 3.616667
boxplot(BD~PreferredOLM,data01)
normality(data01$BD, data01$PreferredOLM, data01)
## T statistic of Raw Data: -0.8929298
## T statistic of Rank Data: -0.8844423
## Difference: 0.008487499
##
## Decision: Assume that the variables are normally distirubted and use T-test. Check the number of observations per group
data01 %>%
group_by(PreferredOLM) %>%
dplyr::summarise(N=length(CD), Mean=mean(CD), SD=sd(CD))
## # A tibble: 2 x 4
## PreferredOLM N Mean SD
## <chr> <int> <dbl> <dbl>
## 1 Asynchronous 39 3.77 0.615
## 2 Synchronous 20 3.88 0.576
t.test(CD~PreferredOLM, data01, var.equal = FALSE)
##
## Welch Two Sample t-test
##
## data: CD by PreferredOLM
## t = -0.65228, df = 40.77, p-value = 0.5179
## alternative hypothesis: true difference in means between group Asynchronous and group Synchronous is not equal to 0
## 95 percent confidence interval:
## -0.4330097 0.2216137
## sample estimates:
## mean in group Asynchronous mean in group Synchronous
## 3.772080 3.877778
boxplot(CD~PreferredOLM,data01)
normality(data01$CD, data01$PreferredOLM, data01)
## T statistic of Raw Data: -0.6383069
## T statistic of Rank Data: -0.3025862
## Difference: 0.3357207
##
## Decision: Assume that the variables are normally distirubted and use T-test. Check the number of observations per group
data01 %>%
group_by(PreferredOLM) %>%
dplyr::summarise(N=length(StudentEngagement), Mean=mean(StudentEngagement), SD=sd(StudentEngagement))
## # A tibble: 2 x 4
## PreferredOLM N Mean SD
## <chr> <int> <dbl> <dbl>
## 1 Asynchronous 39 3.55 0.441
## 2 Synchronous 20 3.73 0.388
t.test(StudentEngagement~PreferredOLM, data01, var.equal = FALSE)
##
## Welch Two Sample t-test
##
## data: StudentEngagement by PreferredOLM
## t = -1.6232, df = 43.015, p-value = 0.1119
## alternative hypothesis: true difference in means between group Asynchronous and group Synchronous is not equal to 0
## 95 percent confidence interval:
## -0.40748881 0.04405102
## sample estimates:
## mean in group Asynchronous mean in group Synchronous
## 3.546059 3.727778
boxplot(StudentEngagement~PreferredOLM,data01)
normality(data01$StudentEngagement, data01$PreferredOLM, data01)
## T statistic of Raw Data: -1.557508
## T statistic of Rank Data: -1.506365
## Difference: 0.0511425
##
## Decision: Assume that the variables are normally distirubted and use T-test. Check the number of observations per group