General Help

StatCrunch should run on any of the three major platforms (Mac, PC, Unix). It only has the minimal requirement of a Java-capable Web browser which almost everyone on the Web now has. If you do not have a Java-enabled browser, you will probably see a gray box which may or may not have a red x in it after logging in to StatCrunch. A test to determine if a browser is Java-enabled is given below:

Java -

If the test above indicates that Java is not enabled, perform one of the following:

• Go to "Tools | Internet Options..." from the main menu
• Change to the "Security" tab
• Click "Custom Level..." button
• To enable: make sure a setting other than "Disable Java" is selected under "Java." If you're not sure which setting to choose, select "High safety"
• Restart the browser

• Go to "View | Internet Options..." from the main menu
• Change to the "Security" tab
• Select "Custom" and click on the "Settings..." button
• To enable: make sure a setting other than "Disable Java" is selected under "Java." If you're not sure which setting to choose, select "High safety"
• Restart the browser

• Go to "Edit | Preferences..." from the main menu
• Select "Advanced" panel
• To enable: make sure "Enable Java" check box is checked.
  
• Restart the browser

• Go to "Options | Network Preferences..." from the main menu
• Change to the "Languages" tab
• To enable: make sure "Enable Java" check box is checked
  
• Restart the browser

The dataset to be analyzed is displayed inside the data table located below the menu bar. StatCrunch offers a variety of methods for loading data. After loading data and selecting a menu item, a listing of the available procedures will appear in a new window. A dialog box will appear after selecting one of these procedures. In the dialog box will be a ? button which directly links the user to the relevant help information for that procedure. After making selections within the dialog box, the results of the procedure will appear in the window.

<A href="http://www.statcrunch.com/">StatCrunch</A>

1. Simply specify the text of the link to be displayed on the web page (e.g., "My Data File").
2. Specify the WWW address of the dataset to be loaded (e.g., http://www.myData.com/myData.txt).
3. If the first line of the data file contains variable names, check the Use first line as variable names option.
4. If the data file is a text file, specify the delimiter for the observations. The delimiter options are whitespace (any whitespace character such as a space or tab), tab, comma (for .csv files) and semicolon.

Calories=190

includes rows where the Calories column is equal to 190

Calories>150

includes rows where the Calories column is greater than 150

Calories>=150

includes rows where the Calories column is greater than or equal to 150

Calories<>190

includes rows where the Calories column is not equal to 190

Calories!=190

includes rows where the Calories column is not equal to 190

LOG(Calories)>5

includes rows where the natural logarithm of the Calories column is greater than 5

Type=Meat

includes rows where the text in the Type column is Meat.

Type="Meat"

includes rows where the text in the Type column is Meat. Note that it is only necessary to use double quotes when the text string contains spaces.

Type<>Beef

includes rows where the text in the Type column is not Beef.

Sodium=386 AND Type=Meat

includes rows where the Sodium column is equal to 386 and the Type column is Meat

Sodium<=400 OR Type="Meat"

includes rows where the Sodium column is less than or equal to 400 or the Type column is Meat

(Sodium>=400 OR Sodium<=500) AND Type="Meat"

includes rows where the Sodium column is between 400 and 500 and the Type column is Meat

row=5

includes only the 5th row

row>=3 AND row<=10

includes rows 3 through 10

• Most expressions should contain references to the existing columns in the data table. If there is a column name that contains a space, references to the column need to be enclosed in double quotes (e.g., "Column One").
• Row may be used to refer to the row id column in the data table. This is a StatCrunch keyword, so any other columns given this name will not be properly referenced.
• Parentheses can be used to force the order of evaluation in both mathematical and boolean expressions.
• The syntax for StatCrunch expressions follows ANSI SQL syntax. The components that can be used in an expression are listed below.
  • Comparison Operators

    These operators below are very useful when constructing boolean expressions for Where statements.

    =

    tests for equality of numeric or text values

    >

    tests if one numeric value is greater than another numeric value

    <

    tests if one numeric value is less than another numeric value

    >=

    tests if one numeric value is greater than or equal to another numeric value

    <=

    tests if one numeric value is less than or equal to another numeric value

    <>

    tests for nonequality of values

    !=

    tests for nonequality of values

    IS NULL

    tests for a null value (empty cell)

    IS NOT NULL

    tests for a nonnull value

  • Logical Operators

    These operators below are very useful when constructing boolean expressions for Where statements.

    AND

    compares two boolean values, returns true if both are true, and false otherwise

    OR

    compares two boolean values, returns true if either is true, and false otherwise

  • Arithmetic Operators

    These operators return numeric results when used with numeric arguments and null values otherwise.

    /

    divides two numeric values

    *

    multiplies two numeric values

    +

    adds two numeric values

    -

    subtracts two numeric values

    **

    exponentiates one numeric value by another

    ^

    Same as ** above.

  • Comparison Functions

    The functions below produce boolean (true/false) outputs. You can specify columns names as inputs in which case the function will return a vector applying the function to each value in the input column.

    between(x,y,z)

    returns true if x is between y and z (noninclusive) and false otherwise

    ifelse(x,y,z)

    returns y if x is true and z otherwise

    ifnull(x,y,z)

    returns y if x is null (empty) and z otherwise

    isNaN(x)

    returns true if x is not a numeric value and false otherwise

    isNull(x)

    returns true if x is null and false otherwise

  • Mathematical Functions

    The functions below require numeric inputs and provide numeric outputs. StatCrunch attempts to coerce nonumeric values into the correct input type. You can specify columns names as inputs in which case the function will return a vector applying the function to each value in the input column.

    abs(x)

    absolute value

    acos(x)

    arc cosine

    asin(x)

    arc sine

    atan(x)

    arc tangent

    ceil(x)

    ceiling, round up

    cos(x)

    cosine

    dbeta(x,alpha,beta)

    beta distribution function at the value x with shape alpha and scale beta

    dbinom(x,n,p)

    binomial distribution function at the value x with parameters n and p

    dcauchy(x)

    cauchy density at the value x with location 0 and scale 1

    dchisq(x,df)

    chi-square density at the value x with degrees of freedom df

    df(x,ndf,ddf)

    F density at the value x with numerator degrees of freedom ndf and denominator degrees of freedom ddf

    dgamma(x,alpha)

    gamma density at the value x with shape alpha

    dnorm(x,mu,sigma)

    normal density at the value x with mean of mu and standard deviation sigma

    dpois(x,lambda)

    Poisson distribution function at the value x with mean lambda

    dt(x,df)

    t density at the value x with degrees of freedom df

    exp(x)

    exponent

    floor(x)

    truncates to nearest integer

    larger(x,y)

    returns the larger of x and y

    lesser(x,y)

    returns the lesser of x and y

    lngamma(x)

    natural logarithm of the gamma function

    log(x)

    natural logarithm

    log10(x)

    logarithm base 10

    log2(x)

    logarithm base 2

    logbeta(x,y)

    natural logarithm of the beta function

    ln(x)

    natural logarithm base e

    pbeta(x,alpha,beta)

    beta CDF at the value x with shape alpha and scale beta

    pbinom(x,n,p)

    binomial CDF at the value x with parameters n and p

    pcauchy(x)

    cauchy CDF at the value x with location 0 and scale 1

    pchisq(x,df)

    chi-square CDF at the value x with degrees of freedom df

    pf(x,ndf,ddf)

    F CDF at the value x with numerator degrees of freedom ndf and denominator degrees of freedom ddf

    pgamma(x,alpha)

    gamma CDF at the value x with shape alpha

    pnorm(x,mu,sigma)

    normal CDF at the value x with mean of mu and standard deviation sigma

    ppois(x,lambda)

    Poisson CDF at the value x with mean lambda

    pt(x,df)

    t CDF at the value x with degrees of freedom df

    qbeta(x,alpha,beta)

    beta quantile at the value x (between 0 an 1) with shape alpha and scale beta

    qbinom(x,n,p)

    binomial quantile at the value x (between 0 an 1) with parameters n and p

    qcauchy(x)

    cauchy quantile at the value x (between 0 an 1) with location 0 and scale 1

    qchisq(x,df)

    chi-square quantile at the value x v with degrees of freedom df

    qf(x,ndf,ddf)

    F quantile at the value x (between 0 an 1) with numerator degrees of freedom ndf and denominator degrees of freedom ddf

    qgamma(x,alpha)

    gamma quantile at the value x (between 0 an 1) with shape alpha

    qnorm(x,mu,sigma)

    normal quantile at the value x (between 0 an 1) with mean of mu and standard deviation sigma

    qpois(x,lambda)

    Poisson quantile at the value x (between 0 an 1) with mean lambda

    qt(x,df)

    t quantile at the value x (between 0 an 1) with degrees of freedom df

    rbeta(n,alpha,beta)

    beta sample of size n with shape alpha and scale beta

    rbinom(n,size,p)

    binomial sample of size n with parameters size and p

    rcauchy(n)

    cauchy sample of size n with location 0 and scale 1

    rchisq(n,df)

    chi-square sample of size n with degrees of freedom df

    rf(n,ndf,ddf)

    F sample of size n with numerator degrees of freedom ndf and denominator degrees of freedom ddf

    rgamma(n,alpha)

    gamma sample of size n with shape alpha

    rnorm(n,mu,sigma)

    normal sample of size n with mean of mu and standard deviation sigma

    round(x)

    rounds to nearest integer

    rpois(n,lambda)

    Poisson sample of size n with mean lambda

    rt(n,df)

    t sample of size n with degrees of freedom df

    sin(x)

    sine

    sqrt(x)

    square root

    tan(x)

    tangent

  • String Functions

    The functions below require string (text) inputs. StatCrunch attempts to coerce nonstring values into the correct input type. You can specify columns names as inputs in which case the function will return a vector applying the function to each value in the input column.

    contains(x,y)

    returns true if the string x contains the string y and false otherwise

    endsWith(x,y)

    returns true if the string x ends with the string y and false otherwise

    indexOf(x,y)

    returns the first numeric index in the string x where the string y occurs (starting at index of 0), returns -1 if x does not contain y

    lastIndexOf(x,y)

    returns the last numeric index in the string x where the string y occurs (starting at index of 0), returns -1 if x does not contain y

    length(x)

    returns the length of the string x

    replace(x,y,x)

    replaces all occurrences of y with z in x

    startsWith(x,y)

    returns true if the string x starts with the string y and false otherwise

    substring(x,y)

    returns the substring of x beginning at y (starting at index of 0)

  • Column Functions

    The functions below have a column name(s) as an argument(s) and return numeric values or vectors. The function names are not case sensitive.

    count(x)

    returns the number of values in the column

    cor(x,y)

    correlation between x and y

    cov(x,y)

    covariance between x and y

    max(x)

    returns the maximum of the column

    mean(x)

    returns the mean of the column

    median(x)

    returns the median of the column

    min(x)

    returns the minimum of the column

    percentile(x,p)

    returns the pth percentile of x

    range(x)

    returns the range of the column

    rep(x,y)

    returns each value in x repeated a corresponding number of y times (with all sequences stacked)

    seq(x,y,z)

    returns the sequence of values from x to y by z (with all sequences stacked)

    sort(x)

    returns the sort of the column

    std(x)

    returns the standard deviation of the column

    sum(x)

    returns the sum of the column

    var(x)

    returns the variance of the column

  • Row Functions

    The functions below require a comma delimited list of column names (...) as an argument and returns in most cases a vector of values for each row.

    pconcat(...)

    row wise string concatenation

    pmax(...)

    row wise maximum

    pmean(...)

    row wise mean

    pmin(...)

    row wise minimum

    pvar(...)

    row wise variance

    concat(...)

    stacks all values into a single column

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  Using GROUP BY

  Most StatCrunch analysis procedures allow the user to group results based on a column in the data table. For example, to compute summary statistics of Calories grouped by Type using the Hotdog Data, select Calories under Select column(s) and Type as the "Group by" variable. This will return summary statics for each distinct value of Type.

  Some of the graphics provide an option to view separate graphs for each group. This option is not selected by default. If this option is not chosen, then the plot will be color coded based on the grouping variable for easy reference.

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  Fonts

  StatCrunch allows the user to specify the three separate fonts that are used to display the data table, text results (tabular results), and graphical results. To specify these fonts, use the Edit > Fonts menu option, and then specify the name/size for each of the fonts. Note that the available fonts may vary depending on the fonts available on the user's computer system. Also, note that the font specified for graphical results is the maximum font size that may be used. When constructing graphics, StatCrunch may shrink the font in order to fit the graphic nicely in a standard sized result window. The corresponding result window may be manually resized to increase the font size up to the maximum font specified for graphics.

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  Orderings

  StatCrunch allows the user to create orderings that are used to determine the display order for certain types of tabular and graphical output. An ordering can be specified to help StatCrunch display output in a more natural way. As examples, StatCrunch provides predefined orderings for both the natural ordering of the days of week (Sunday,Monday,Tuesday,... and Sun,Mon,Tue,...) and the natural ordering of the months of the year (January,February,March,... and Jan,Feb,Mar,...). When StatCrunch produces output with a set of group labels that contains only the values defined in an ordering or some subset of them, the groups will be reordered in the output according to their relative position in the ordering sequence rather than using an alphanumeric ordering which is otherwise standard.

  Orderings can be added, deleted and modified using the Edit > Orderings menu option. When this option is selected, a new dialog will appear with a listing of all the active orderings for the current StatCrunch session. To modify/remove a particular ordering, select the ordering from the list and then press the Edit/Delete button. A new ordering can be added by clicking the Add new ordering button. When modifying or adding an ordering, the distinct values should be entered one per line in the resulting text field. StatCrunch ignores case when comparing ordering values to group labels to determine whether or not to apply the ordering to specific output.

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  Contact Us

  With questions or comments please submit a request via the tech support page.