Download Introduction to StatCrunch

Introduction to StatCrunch
Social Science Research Lab
American University, Washington, D.C.
Web: www.american.edu/provost/ctrl/pclabs.cfm
Tel: x3862 Email: [email protected]
Course Objectives
This course will provide students with the necessary tools to work with data using
StatCrunch 5.0.
Learning Outcomes
Getting access to the StatCrunch web platform
Loading new datasets
Getting summary statistics
Running Z Statistics test
Running simple linear regression
Using Normal calculator
Creating graphics: histogram, stem and leaf plot, boxplot, scatter plot
Saving and exporting data
What is StatCrunch?
StatCrunch is a statistical data analysis package for the World Wide Web. It is
written in the form of a Java applet and it is easy to use. StatCrunch should run on
any of the three major platforms (Mac, PC, Unix).
Getting Started
Go to http://statcrunch.american.edu/. Type “eagle” in the Passcode box then
click Submit.
The StatCrunch, Data, Stat, Graphics and Help menus are located at the top of the
StatCrunch frame provide users with access to the analysis procedures of the
software.
Load Data from File
Go to Data > Load Data > from file > Browse > choose a text or excel file from local
computer > Okay
Here, we will load a dataset from StatCrunch for the purpose this tutorial. Eg. Go to
Data > Load Data > from Sample Data > StatCrunch > Select Stat 110 Class Data >
Okay
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Load Data from Paste
You can also copy and paste data copied from an excel spreadsheet
Go to Data > Load Data > From paste > click “paste data from clipboard”
At the bottom, if your data columns are labeled (for example, Age, Gender, etc.),
make sure the box “use first column as names” is selected. If not, deselect it.
Summary Statistics
Columns: Provides sample size (n), mean, variance, standard deviation (Std. Dev.),
Standard Error (Std. Err.), median, range, minimum, maximum, first quartile (Q1) and
third quartile (Q3) in tabular format for the column(s) selected
Rows: Provides count, sum, mean, variance, standard deviation, minimum, median
and maximum for each row in the data table for the columns selected
Correlation: Computes the Pearson correlation between two columns
Covariance: Computes the covariance between two columns
Go to Stat > Summary Stats > Columns/Rows/Correlation/Covariance > Select the
columns you want > Next > Calculate
Z Statistics for One Sample
Provides hypothesis tests and confidence intervals for a population mean based on
a single sample when the population variance is known
Go to Stat > Z Statistics > One Sample > With Data > Select the columns you want
(GRADE in this case) > Next > Check Hypothesis Test> Enter a null value for the
population mean > Choose from the options of ≠, < and > for the alternative
hypothesis > Calculate
The null hypothesis and the options of ≠, <, or > depends on the specific proposition
you want to test. In this case, whether the mean grade of the sample = 85 or not.
Sample Output:
You can also sort your data by category. For example, if you want to see the same
statistics but separated by sex:
Go to Go to Stat > Z Statistics > One Sample > With Data > Select the columns you
want (GRADE in this case) > click the drop down “group by” option > select sex >
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Next > Check Hypothesis Test> Enter a null value for the population mean > Choose
from the options of “≠”, “<” and “>” for the alternative hypothesis > Calculate
Hypothesis test results:
Group by: SEX
μ : mean of GRADE
H0 : μ = 85
HA : μ ≠ 85
Std. Dev. not specified.
SEX n
Sample Mean
Std. Err.
Z-Stat
P-value
F
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85.85294 2.933345
0.29077423
0.7712
M
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77.933334 4.416284
-1.6001387
0.1096
Calculating the Confidence Interval
Go to Stat > Z Statistics > One Sample > With Data > Select the columns you want
(GRADE in this case) > Next > Check Confidence Interval > Enter 0.95 in Level
Sample Output:
Simple Linear Regression
Provides routines for fitting the simple linear regression model
A regression line measures the least squared distance between x (the independent
variable) and y (the dependent variable). It will tell you, given a change in x, how
much y will change. R squared is the percentage of change in y that can be
explained by changes in x.
Go to Stat > Regression > Simple Linear > Select the X variable (independent) for the
regression (GRADE in this case) > Select the Y variable (dependent) for the
regression (STUDY in this case) > Next > check “Save residuals” > Next > Check “Plot
the fitted line” > Calculate
Sample Output:
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Normal Distribution Calculator
Calculate the probability of specified Z score:
Go to Stat > Calculators > Normal > Enter mean and standard deviation > Select
“>=” or “<=” > Enter Z score > Compute
Calculate the Z score of specified probability:
Go to Stat > Calculators > Normal > Enter mean and standard deviation > Select
“>=” or “<=” > Enter probability (between 0 and 1) > Compute
Graphics
Histogram
Displays the frequency, relative frequency or density for numerical data
Go to Graphics > Histogram > Select the columns you want > Next > Next > Create
Graph!
Stem and Leaf
Displays a character based plot of a column that is similar to a histogram on its side
Go to Graphics > Stem and Leaf > Select the columns you want > Create Graph!
Boxplot
Displays a graphical representation of the 5-number summary for a set of numerical
values, or optionally, a boxplot using inner and outer fences
Go to Graphics > Boxplot > Select the columns you want > check “Use fences to
identify outliers” > Next* > Next > Create Graph!
Scatter Plot
Displays pairs of numerical values (points) on typical Cartesian (perpendicular) axes
Go to Graphics > Scatter Plot > Select the column containing the X-values > Select
the column containing the Y-values > Next > Next* > Create Graph!
*Here you can change the labels on the x and y axes and/or add a title if you want
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Saving Results
When you’ve reached the final results screen or graph for the calculation you’re
doing:
Go to the Options menu > Select Export or Copy > export or paste to word,
PowerPoint, etc.
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