Statistic Assignment
Danyah
stat_lab_2-1.pptxLAB 2:
Descriptive Statistics
1
Descriptive statistics are numerical estimates that organize and sum up or present the data.
For quantitative variables (scale)
Mean with Standard deviation are used to summarize non-skewed scale variables
Median with range or interquartile range are used to summarize skewed scale variables
The three steps to evaluate the normality assumption are:
Compare the statistics values ( mean versus median)
Obtain the histogram with normal curve
Obtain the Box-Whiskers plot
For this class,
If there is any extreme outliers, median with range should be used to summarize the variable of interest
If there is any outliers (regular outliers), you need to based your decision regarding the best measure (mean with SD or median with range) to summarize the variable of interest on the shape of the histogram
Introduction
2
For qualitative variable (nominal or ordinal)
Frequency distributions (number with percentages) are used to summarize qualitative variables
Descriptive statistics for multiple groups:
Use Split file option in SPSS to obtain the measures of central tendency and the measures of variation for quantitative variables.
After you split your file by the grouping variable, you should follow the previous steps to select the most appropriate measures to summarize your variable of interest.
Please note that you have to un-split the data before running further analysis
Use Crosstabs option in SPSS to obtain the frequency distributions (number with percentages) for the qualitative variables
Introduction
3
4
Types of variables
Continuous (Quantitative) Variables
Qualitative (Categorical) Variables
Nominal/ Ordinal
Interval/Ratio
Number and Percent
N (%)
Normal distribution
1- Statistics {Mean and Median}
2- Histogram with Normal Curve
3- Box-Whiskers Plot
No
Median with Range
Yes
Mean with Standard Deviation
Box-Whiskers Plot
5
6
7
Box-Whiskers Plot
Source: http://support.sas.com/documentation/cdl/en/statug/63347/HTML/default/viewer.htm#statug_boxplot_sect017.htm
8
Extreme outliers (values greater than 3 IQR from Q1/Q3)
Outliers (values between 1.5 and 3 IQRs from Q1/Q3)
Whisker extends to furthest observation within Q3 + 1.5*IQR
Whisker extends to furthest observation within Q1 - 1.5*IQR
9
Example
Types of Variables
Procedures
Un-split the data before running further analysis
Descriptive Statistics for Multiple Groups
10
Split File
Qualitative or Categorical Variable (Grouping variable)
Crosstabs
Qualitative or Categorical Variable
Qualitative or Categorical Variable
Continuous or Quantitative Variable
Men (Gender)
Baseline Pulse
Females (Gender)
Widowed (Marital Status)
Example:
Following is a dictionary for a data set. The data collected on a number of people from Cornwall, Ontario, Canada who attended a lifestyle intervention program (Coronary Health Improvement Project, or better known as CHIP) consisting of a series of lectures and personal counseling sessions every day for a five day period. This data set consists of a number of demographic and clinical variables. Create the lifestyle dataset using the table below and answer the following questions.
Variable View
Data View
| Table 1 | |||
| Variable | Mean ± SD | Median (Range) | N (%) |
| Age | |||
| Exercise | |||
| Smoke | |||
| Weight | |||
| Glucose |
Question1: Summarize using the most appropriate measure the following variables presented in the Table 1.1. Choose either the mean, median or n(%) as the most appropriate measure for each variable.
Answer: 1.1
For quantitative variables:
Step1: Compare statistics values (mean versus median) for all variables
Step2: Evaluate the normal curve
Answer: 1.1
For quantitative variables:
Step3: Evaluate the Box - Whiskers Plot
| Variable | Statistics (mean vs. median | Histogram with normal curve | Box- Whiskers Plot | Decision |
| Age | Close | Normal | One regular outlier (no extreme outliers) | Mean ± SD |
| Weight | Close | Normal | No outliers | Mean ± SD |
| Glucose | Close | Skewed | Extreme outlier | Median (Range) |
Normality Assumption Checklist
For qualitative variables
Question1: Summarize using the most appropriate measure the following variables presented in the Table 1.1.
Question2: Summarize using the most appropriate measure the following variables presented in the Table 1.2.
Step1: Split file by grouping variable (Gender)
Question2: Summarize using the most appropriate measure the following variables presented in the Table 1.2.
Step2: Compare statistics values (mean versus median) for all variables
Question2: Summarize using the most appropriate measure the following variables presented in the Table 1.2.
Step3: Evaluate the normal curve
Male
Female
Question2: Summarize using the most appropriate measure the following variables presented in the Table 1.2.
Step4: Evaluate the Box - Whiskers Plot
Male
Female
Question2: Summarize using the most appropriate measure the following variables presented in the Table 1.2.
Note: Un-split the data file before running further analysis
Question3: Summarize using the most appropriate measure the following variables presented in the Table 1.3.
| Qualitative Variables | Male : n (%) | Female : n (%) |
| Frame Small | ||
| Medium | ||
| Large | ||
| Exercise: None | ||
| Mild | ||
| Moderate | ||
| Vigorous |
Question3: Summarize using the most appropriate measure the following variables presented in the Table 1.3.
Step1: Use Crosstabs option in SPSS to obtain the frequency distributions for the qualitative variable by the grouping variable
Question3: Summarize using the most appropriate measure the following variables presented in the Table 1.3.
| Qualitative Variables | Male : n (%) | Female : n (%) |
| Frame Small | 0 (0.0) | 0 (0.0) |
| Medium | 4 (40.0) | 6 (60.0) |
| Large | 6 (60.0) | 4 (40.0) |
| Exercise: None | 4 (40.0) | 6 (60.0) |
| Mild | 1 (10.0) | 0 (0.0) |
| Moderate | 3 (30.0) | 3 (30.0) |
| Vigorous | 2 (20.0) | 1 (10.0) |
Table 1.1
Variables
Mean ± SD
Median (Range)
N (%)
Age
51.60 ± 12.75
Baseline Weight 176.55 ± 38.46
Baseline Glucose
5.25 (5)
Exercise:
None
Mild
Moderate
Vigorous
10 (50.0)
1 (5.0)
6 (30.0)
3 (15.0)
Smoking Status:
Non-smoker
Smoker
20 (100.0)
0 (0.0)
|
Table 1.1 |
|||
|
Variables |
Mean ± SD |
Median (Range) |
N (%) |
|
Age |
51.60 ± 12.75 |
|
|
|
Baseline Weight |
176.55 ± 38.46 |
|
|
|
Baseline Glucose |
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5.25 (5) |
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|
Exercise: None Mild Moderate Vigorous |
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|
10 (50.0) 1 (5.0) 6 (30.0) 3 (15.0) |
|
Smoking Status: Non-smoker Smoker |
|
|
20 (100.0) 0 (0.0) |
Males n =
Females n =
Quantitative Variables
Mean ± SD Median (Range)
Mean ± SD Median (Range)
Age
Baseline Weight
Baseline Glucose
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Males n = |
Females n = |
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Quantitative Variables |
Mean ± SD Median (Range) |
Mean ± SD Median (Range) |
|
Age |
|
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Baseline Weight |
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Baseline Glucose |
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Males n = |
Females n = |
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Quantitative Variables |
Mean ± SD Median (Range) |
Mean ± SD Median (Range) |
|
Age |
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|
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Baseline Weight |
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|
|
Baseline Glucose |
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Males n =10
Females n =10
Quantitative Variables
Mean ± SD Median (Range)
Mean ± SD Median (Range)
Age
56.1 ± 14.3
47.1 ± 9.6
Baseline Weight
189.3 ± 35.8
150.5 (132)
Baseline Glucose
5.5 (5)
5.01 (1.7)
|
|
Males n =10 |
Females n =10 |
|
Quantitative Variables |
Mean ± SD Median (Range) |
Mean ± SD Median (Range) |
|
Age |
56.1 ± 14.3 |
47.1 ± 9.6 |
|
Baseline Weight |
189.3 ± 35.8 |
150.5 (132) |
|
Baseline Glucose |
5.5 (5) |
5.01 (1.7) |
