TA Lab Section & Time
Amy White LAB 104 M 12:30-2:20 pm in PHY 145
Arisha Imran LAB 102 M 2:30-4:20 pm in PHY 145
Xuewen Geng LAB 105 W 12:30-2:20 pm in PHY 145
Amy Lacey LAB 106 Th 2:30-4:20 pm in STC 0050
Luke Schofield LAB 103 F 12:30-2:20 pm in PHY 145
Ashley Ferns LAB 101 F 2:30-4:20 pm in PHY 145
MAKE SURE TO WORK THROUGH LECTURE 4 BEFORE PARTICIPATING IN LAB 1.
Before attending the lab, you must secure access to IBM-SPSS version 29/30 software using one of the two
options detailed in the course Outline. Make sure you have SPSS open and running when the lab session
begins. Note: for access to SPSS using Option 2, the university loaded version 30 of SPSS after Prof. Hall
wrote the Course Outline. Versions 29 and 30 should be virtually identical.
Objectives: In this lab, you’ll learn basic features of IBM-SPSS that will be useful for this lab, future labs and
assignments. You’ll learn to use SPSS to perform descriptive statistics by applying it to two data sets collected
in 2019.
Part A: Getting started in SPSS – no Answers beyond the information provided in the Instruction file. By the
end of Part A, students will have the data used in Part B loaded into an SPSS data file and saved as
‘Height_Armspan_2019.sav’. If you followed the instructions, the .sav file will have the correct ‘Type’, number
of decimal places, and an informative ‘Label’ including the unit of measurement identified for each variable.
Part B: Perform descriptive statistics on the data recorded on the gender, height and armspan of students in
BIOL 361, using the SPSS file you generated in Step A.
The file contains the following 4 variables: [Go over the structure of the data (the data were not organized
with male and female values in separate columns! Instead, all heights are in 1 column and code for gender in
another column]
Year = Year of study (2019)
Gender = Gender of student (m = male, f = female) [enter right-hand text into ‘Variable View’ tab]
Height = Height (cm) [enter right-hand text into ‘Variable View’ tab]
Armspan = Armspan length (cm) [enter right-hand text into ‘Variable View’ tab]
1) Compute the summary statistics of central tendency and spread (i.e., mean, median, minimum, maximum,
variance, standard deviation, interquartile range, skewness, kurtosis) for each of the quantitative variables
in the dataset [hint: there are two quantitative variables → Height & Armspan].
Analyze → Descriptive statistics → Explore→ Display = ‘Statistics’ → move variable(s) to dependent list
Or [better], to complete parts 1) and 2) in one step:
Analyze → Descriptive statistics → Explore→ Display = ‘Both’ → move variable(s) to dependent list AND Click
‘Plots’ button and choose ‘histogram’
• Note that when you perform this step, a second window (or file) opens up called Output 1 (by default).
All computations you perform in SPSS get placed into this type of output file (*.spv). You can Save this
file as Height_Armspan_2019.spv
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, Table 1. Tabular Output obtained (the numerical summary statistics):
[Note: the tables produced by SPSS are not in adequate format for your Assignment Reports. See the Course
Handout and Lecture 4 file for examples of how to format a Table and to craft and place a Table Caption. The
SPSS tables do not show the correct number of decimal places according to the Rounding-off rule – you have
to do this! Measurements were made to the nearest 0.5 cm, so minimum and maximum should be presented
to 1 decimal place, and calculated summary statistics (mean, standard deviation, variance, etc.) should be
presented to 2 decimal places (1 more decimal place than the ‘raw’ data). Since there are 157 subjects (an
odd number), the median is a value from a single subject, and should be presented to one decimal place.
Note that if the sample size had been an even number (e.g., 156 or 158), the median value would be an
average of the two middle values and should be presented to 2 decimal places.]
Information that can be gleaned from the Table of summary statistics: The above table presents the key
summary statistics for central tendency (mean, median), spread (standard deviation, variance, interquartile
range, range, minimum, maximum) and shape (skewness, kurtosis). For both variables, the mean is slightly
larger than the median, and values of skewness is slightly greater than zero, suggesting a distribution that is
close to symmetrical or slightly skewed to the right. The means for height and armspan seem to be quite
similar (<1.5 cm difference) when considering that values for each variable span a range of 44-51.5 cm for the
two variables, respectively.
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