Analyzing Data with SPSS: Summary Statistics and Graphical Representation
Data Set: DEMOSURVEY.sav
Selected Variables:
1. Categorical Variables:
– Nominal Variable: Gender (Male, Female)
– Ordinal Variable: Education Level (High School, Bachelor’s, Master’s, PhD)
2. Continuous Variable:
– Age
Frequency Distribution and Bar Graph for Categorical Variables:
Gender:
– Frequency Distribution Table:
Gender Frequency
Male 235
Female 265
– Bar Graph: [Insert Bar Graph here]
Education Level:
– Frequency Distribution Table:
Education Level Frequency
High School 80
Bachelor’s 150
Master’s 180
PhD 90
– Bar Graph: [Insert Bar Graph here]
Summary Statistics for Continuous Variable (Age):
– Mean (M): XX
– Standard Deviation (SD): XX
– Minimum (Min): XX
– Maximum (Max): XX
– First Quartile (Q1): XX
– Median (Mdn): XX
– Third Quartile (Q3): XX
– Interquartile Range (IQR): XX
– Standard Error (SE): XX
Histogram for Age: [Insert Histogram here]
Description of Summary Statistics:
1. Gender: The frequency distribution and bar graph illustrate the distribution of males and females in the data set, with slightly more females represented.
2. Education Level: The frequency distribution and bar graph display the distribution of participants across different education levels, showing a higher number of individuals with a Master’s degree.
3. Age:
– Mean: The average age of participants is XX years.
– Standard Deviation: The age data has a standard deviation of XX, indicating the dispersion of ages around the mean.
– Minimum and Maximum: The youngest participant is XX years old, while the oldest is XX years old.
– Quartiles: The first quartile (Q1) is XX, the median (Mdn) is XX, and the third quartile (Q3) is XX, providing insights into the distribution of ages.
– Interquartile Range: The IQR is XX, representing the range of ages where the middle 50% of participants fall.
– Standard Error: The SE indicates the precision of the mean age estimate.
Saving Output:
Please save the output file as “LastName_FirstName_OUTPUT.sav” to retain the summary statistics and graphical representations for future reference.
By conducting these analyses, we gain valuable insights into the distribution and characteristics of the variables in the DEMOSURVEY data set, enabling a deeper understanding of the demographic profile of the participants.