Attaching package: 'dplyr'The following objects are masked from 'package:stats':
filter, lagThe following objects are masked from 'package:base':
intersect, setdiff, setequal, uniontibble [60 × 24] (S3: tbl_df/tbl/data.frame)
$ Respondents : num [1:60] 1 2 3 4 5 6 7 8 9 10 ...
$ Type of Family: chr [1:60] "Broken Family" "Broken Family" "Broken Family" "Broken Family" ...
$ Sex : chr [1:60] "Male" "Male" "Male" "Male" ...
$ Age : num [1:60] 18 17 17 19 18 18 18 18 18 18 ...
$ RSES 1 : chr [1:60] "Strongly Agree" "Disagree" "Disagree" "Agree" ...
$ RSES 2 : chr [1:60] "Agree" "Strongly Agree" "Agree" "Agree" ...
$ RSES 3 : chr [1:60] "Agree" "Agree" "Agree" "Agree" ...
$ RSES 4 : chr [1:60] "Agree" "Agree" "Disagree" "Agree" ...
$ RSES 5 : chr [1:60] "Disagree" "Agree" "Disagree" "Agree" ...
$ RSES 6 : chr [1:60] "Disagree" "Agree" "Agree" "Disagree" ...
$ RSES 7 : chr [1:60] "Disagree" "Agree" "Agree" "Agree" ...
$ RSES 8 : chr [1:60] "Strongly Agree" "Strongly Agree" "Agree" "Agree" ...
$ RSES 9 : chr [1:60] "Disagree" "Agree" "Disagree" "Agree" ...
$ RSES 10 : chr [1:60] "Agree" "Disagree" "Agree" "Agree" ...
$ RSES1.1 : chr [1:60] "3" "1" "1" "2" ...
$ RSES1.3 : chr [1:60] "2" "2" "2" "2" ...
$ RSES1.4 : chr [1:60] "2" "2" "1" "2" ...
$ RSES1.7 : chr [1:60] "1" "2" "2" "2" ...
$ RSES1.10 : chr [1:60] "2" "1" "2" "2" ...
$ RSES1.2 : chr [1:60] "1" "0" "1" "1" ...
$ RSES1.5 : chr [1:60] "2" "1" "2" "1" ...
$ RSES1.6 : chr [1:60] "2" "1" "1" "2" ...
$ RSES1.8 : chr [1:60] "0" "0" "1" "1" ...
$ RSES1.9 : chr [1:60] "2" "1" "2" "1" ... Min. 1st Qu. Median Mean 3rd Qu. Max.
16.00 18.00 18.00 18.22 18.00 22.00 #Type of Family
`summarise()` has grouped output by 'Type of Family'. You can override using
the `.groups` argument.#Age
`summarise()` has grouped output by 'Age Group'. You can override using the
`.groups` argument.`summarise()` has grouped output by 'Sex'. You can override using the `.groups`
argument.`summarise()` has grouped output by 'Type of Family'. You can override using
the `.groups` argument.
F test to compare two variances
data: Durias$SumSelfEsteem by Durias$`Type of Family`
F = 0.98022, num df = 29, denom df = 29, p-value = 0.9575
alternative hypothesis: true ratio of variances is not equal to 1
95 percent confidence interval:
0.4665496 2.0594353
sample estimates:
ratio of variances
0.9802187 The variances are equal since the p-value exceeds 0.05.
Two Sample t-test
data: Durias$SumSelfEsteem by Durias$`Type of Family`
t = -1.6432, df = 58, p-value = 0.1057
alternative hypothesis: true difference in means between group Broken Family and group Intact Family is not equal to 0
95 percent confidence interval:
-3.4751380 0.3418047
sample estimates:
mean in group Broken Family mean in group Intact Family
15.86667 17.43333 The result shows that the self-esteem between intact and broken family does not statistically differ since the p-value=0.1057 exceeds the 0.05 level of significance.
Cell Contents
|-------------------------|
| N |
| Chi-square contribution |
| N / Row Total |
| N / Col Total |
| N / Table Total |
|-------------------------|
Total Observations in Table: 60
| Durias$`Summary Scale`
Durias$Sex | Non-normal | Normal | Row Total |
-------------|------------|------------|------------|
Female | 12 | 23 | 35 |
| 0.438 | 0.173 | |
| 0.343 | 0.657 | 0.583 |
| 0.706 | 0.535 | |
| 0.200 | 0.383 | |
-------------|------------|------------|------------|
Male | 5 | 20 | 25 |
| 0.613 | 0.242 | |
| 0.200 | 0.800 | 0.417 |
| 0.294 | 0.465 | |
| 0.083 | 0.333 | |
-------------|------------|------------|------------|
Column Total | 17 | 43 | 60 |
| 0.283 | 0.717 | |
-------------|------------|------------|------------|
$t
y
x Non-normal Normal
Female 12 23
Male 5 20
$prop.row
y
x Non-normal Normal
Female 0.3428571 0.6571429
Male 0.2000000 0.8000000
$prop.col
y
x Non-normal Normal
Female 0.7058824 0.5348837
Male 0.2941176 0.4651163
$prop.tbl
y
x Non-normal Normal
Female 0.20000000 0.38333333
Male 0.08333333 0.33333333 Normal Non-normal
Female 23 12
Male 20 5
Pearson's Chi-squared test with Yates' continuity correction
data: table2
X-squared = 0.84659, df = 1, p-value = 0.3575There is no significant relationship between sex and self-esteem level.
Cell Contents
|-------------------------|
| N |
| Chi-square contribution |
| N / Row Total |
| N / Col Total |
| N / Table Total |
|-------------------------|
Total Observations in Table: 60
| Durias$`Summary Scale`
Durias$`Age Group` | Non-normal | Normal | Row Total |
-----------------------|------------|------------|------------|
19 years old and above | 4 | 10 | 14 |
| 0.000 | 0.000 | |
| 0.286 | 0.714 | 0.233 |
| 0.235 | 0.233 | |
| 0.067 | 0.167 | |
-----------------------|------------|------------|------------|
at most 18 years old | 13 | 33 | 46 |
| 0.000 | 0.000 | |
| 0.283 | 0.717 | 0.767 |
| 0.765 | 0.767 | |
| 0.217 | 0.550 | |
-----------------------|------------|------------|------------|
Column Total | 17 | 43 | 60 |
| 0.283 | 0.717 | |
-----------------------|------------|------------|------------|
$t
y
x Non-normal Normal
19 years old and above 4 10
at most 18 years old 13 33
$prop.row
y
x Non-normal Normal
19 years old and above 0.2857143 0.7142857
at most 18 years old 0.2826087 0.7173913
$prop.col
y
x Non-normal Normal
19 years old and above 0.2352941 0.2325581
at most 18 years old 0.7647059 0.7674419
$prop.tbl
y
x Non-normal Normal
19 years old and above 0.06666667 0.16666667
at most 18 years old 0.21666667 0.55000000 Normal Non-normal
at most 18 years old 33 13
at least 19 years old 10 4Warning in chisq.test(table2): Chi-squared approximation may be incorrect
Pearson's Chi-squared test with Yates' continuity correction
data: table2
X-squared = 1.3521e-30, df = 1, p-value = 1There is no significant relationship between age and self-esteem level.