Based on the provided T-test write the narrative describing the results of the t-test.

Please see the analyses bellow:

Included Analyses

• Descriptive Statistics
• Descriptive Statistics
• Descriptive Statistics
• Pie Chart of Gender_code
• Pie Chart of Gender_code
• Scatterplot of Subject_Code_1 and Years_of_Experience_code
• Pie Chart of Gender_code
• Mixed Model ANOVA for Years_of_Experience_code, Pretest_scores, and Posttest_scores by Gender_code

Results

Descriptive Statistics

Introduction

Summary statistics were calculated for Exact_age, Years_of_Experience_code, Pretest_scores, and Posttest_scores.

Summary Statistics

The observations for Exact_age had an average of 38.80 (SD = 7.95, SE_M= 1.45, Min = 26.00, Max = 52.00, Skewness = 0.06, Kurtosis = -1.11). The observations for Years_of_Experience_code had an average of 7.70 (SD = 4.83, SE_M= 0.88, Min = 2.00, Max = 20.00, Skewness = 0.83, Kurtosis = -0.06). The observations for Pretest_scores had an average of 82.60 (SD = 9.53, SE_M= 1.74, Min = 65.00, Max = 98.00, Skewness = -0.14, Kurtosis = -0.81). The observations for Posttest_scores had an average of 87.30 (SD = 7.12, SE_M= 1.30, Min = 75.00, Max = 100.00, Skewness = 0.56, Kurtosis = -0.55). When the skewness is greater than 2 in absolute value, the variable is considered to be asymmetrical about its mean. When the kurtosis is greater than or equal to 3, then the variable's distribution is markedly different than a normal distribution in its tendency to produce outliers (Westfall & Henning, 2013). The summary statistics can be found in Table 1.

Table 1

Summary Statistics Table for Interval and Ratio Variables

Variable	M	SD	n	SEM	Min	Max	Skewness	Kurtosis
Exact_age	38.80	7.95	30	1.45	26.00	52.00	0.06	-1.11
Years_of_Experience_code	7.70	4.83	30	0.88	2.00	20.00	0.83	-0.06
Pretest_scores	82.60	9.53	30	1.74	65.00	98.00	-0.14	-0.81
Posttest_scores	87.30	7.12	30	1.30	75.00	100.00	0.56	-0.55
Note.'-' indicates the statistic is undefined due to constant data or an insufficient sample size.

Descriptive Statistics

Introduction

Summary statistics were calculated for each interval and ratio variable. Frequencies and percentages were calculated for each nominal variable.

Frequencies and Percentages

The most frequently observed category of Gender_code was F (n = 18, 60.00%). Frequencies and percentages are presented in Table 2.

Table 2

Frequency Table for Nominal Variables

Variable	n	%
Gender_code
M	12	40.00
F	18	60.00
Missing	0	0.00
Note.Due to rounding errors, percentages may not equal 100%.

Summary Statistics

The observations for Years_of_Experience_code had an average of 7.70 (SD = 4.83, SE_M= 0.88, Min = 2.00, Max = 20.00, Skewness = 0.83, Kurtosis = -0.06). The observations for Exact_age had an average of 38.80 (SD = 7.95, SE_M= 1.45, Min = 26.00, Max = 52.00, Skewness = 0.06, Kurtosis = -1.11). The observations for Posttest_scores had an average of 87.30 (SD = 7.12, SE_M= 1.30, Min = 75.00, Max = 100.00, Skewness = 0.56, Kurtosis = -0.55). The observations for Pretest_scores had an average of 82.60 (SD = 9.53, SE_M= 1.74, Min = 65.00, Max = 98.00, Skewness = -0.14, Kurtosis = -0.81). When the skewness is greater than 2 in absolute value, the variable is considered to be asymmetrical about its mean. When the kurtosis is greater than or equal to 3, then the variable's distribution is markedly different than a normal distribution in its tendency to produce outliers (Westfall & Henning, 2013). The summary statistics can be found in Table 3.

Table 3

Summary Statistics Table for Interval and Ratio Variables

Variable	M	SD	n	SEM	Min	Max	Skewness	Kurtosis
Years_of_Experience_code	7.70	4.83	30	0.88	2.00	20.00	0.83	-0.06
Exact_age	38.80	7.95	30	1.45	26.00	52.00	0.06	-1.11
Posttest_scores	87.30	7.12	30	1.30	75.00	100.00	0.56	-0.55
Pretest_scores	82.60	9.53	30	1.74	65.00	98.00	-0.14	-0.81
Note.'-' indicates the statistic is undefined due to constant data or an insufficient sample size.

Descriptive Statistics

Introduction

Summary statistics were calculated for each interval and ratio variable. Frequencies and percentages were calculated for each nominal variable.

Frequencies and Percentages

The most frequently observed category of Gender_code was F (n = 18, 60.00%). Frequencies and percentages are presented in Table 4.

Table 4

Frequency Table for Nominal Variables

Variable	n	%
Gender_code
M	12	40.00
F	18	60.00
Missing	0	0.00
Note.Due to rounding errors, percentages may not equal 100%.

Summary Statistics

The observations for Pretest_scores had an average of 82.60 (SD = 9.53, SE_M= 1.74, Min = 65.00, Max = 98.00, Skewness = -0.14, Kurtosis = -0.81). The observations for Exact_age had an average of 38.80 (SD = 7.95, SE_M= 1.45, Min = 26.00, Max = 52.00, Skewness = 0.06, Kurtosis = -1.11). The observations for Posttest_scores had an average of 87.30 (SD = 7.12, SE_M= 1.30, Min = 75.00, Max = 100.00, Skewness = 0.56, Kurtosis = -0.55). The observations for Years_of_Experience_code had an average of 7.70 (SD = 4.83, SE_M= 0.88, Min = 2.00, Max = 20.00, Skewness = 0.83, Kurtosis = -0.06). When the skewness is greater than 2 in absolute value, the variable is considered to be asymmetrical about its mean. When the kurtosis is greater than or equal to 3, then the variable's distribution is markedly different than a normal distribution in its tendency to produce outliers (Westfall & Henning, 2013). The summary statistics can be found in Table 5.

Table 5

Summary Statistics Table for Interval and Ratio Variables

Variable	M	SD	n	SEM	Min	Max	Skewness	Kurtosis
Pretest_scores	82.60	9.53	30	1.74	65.00	98.00	-0.14	-0.81
Exact_age	38.80	7.95	30	1.45	26.00	52.00	0.06	-1.11
Posttest_scores	87.30	7.12	30	1.30	75.00	100.00	0.56	-0.55
Years_of_Experience_code	7.70	4.83	30	0.88	2.00	20.00	0.83	-0.06
Note.'-' indicates the statistic is undefined due to constant data or an insufficient sample size.

Figure 1

Pie Chart of Gender_code