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Version 2.5 Everthing in Version 2.0 plus...
Multiple Language Capability - EZAnalyze, when installed on your computer, will give you the option to view EZAnalyze in English, Spanish, Serbian, or Hungarian through a "Language Options" menu. It also has the built-in ability for you to modify the language EZAnalyze uses in dialog boxes and on output by creating your own "user defined" language. If anyone translates EZAnalyze into a new language, I will make it available through this website. Learn more!
More New Variable Functions - While EZAnalyze was designed for use by educators, it is often used by graduate students and their professors. "New" new variable functions are:
- Standardized (Z) Score - creates a standardized (Z) score based on your selected variable's mean and standard deviation, or you can specify the mean and standard deviation you would like to use
- Percentile Rank - creates a percentile rank for each score in the variable you choose from your data. This can be very useful for counselors who need to calculate rank in class!
- Binary Variable - creates a set of binary (0-1) variables from a single variable. This is useful, for example, if you want to compare 9th grade students to all other students - you could create a binary variable that is a "1" for all students in your data where they have a 9 on the grade variable.
- Random Numbers - creates a new variable containing random numbers. The numbers can be truly random within a range that you specify, or can be "normally" distributed based on a mean and standard deviation you specify. Very useful for quickly and easily generating some data to play with!
Multiple Variable Graphing - Now you can create a graph comparing multiple variables side-by-side. You can also create error bar graphs using this new feature!
Repeated Measures ANOVA - A standard repeated measures ANOVA function is now available
Post Hoc tests for ANOVA functions - For both the single factor ANOVA and the repeated measures ANOVA, simple post hoc tests are performed if the omnibus F test is significant.
Delete Xtra Sheets - Now you can quickly and easily delete the sheets that pile up when you use EZAnalyze with a single click.
Several other enhancements were also made to improve both the functionality and appearance of EZAnalyze.
Version 2.0
EZAnalyze contains all of the functions necessary to generate results reports to engage in data-based decision making and program evaluation at the classroom, school, and district levels.
DESCRIBE: Allows you to obtain percentages for your variables. For example, if you have an "ethnicity" variable, this function will give you the percentage of each ethnic group. You can also calculate descriptive statistics - mean, standard deviation, minimum and maximum scores, and range. For each function, you can select multiple variables.
DISAGGREGATE: Allows you to disaggregate a "dependent variable" by one or two "categorical variables." The best example of this would be disaggregating an academic achievement variable (dependent) by ethnicity (categorical) and gender (categorical). You can select multiple dependent variables.
GRAPH: Permits easy creation of "histogram" graphs and "disaggregation" graphs. A histogram can be used to show you the "shape" of your distribution with an area or bar chart, or show you how many people fall into each category with a pie chart. The disaggregation graph allows you to create bar or area charts to display disaggregated data.
NEW VARIABLE: Allows you to quickly and easily create a new summary variable that is the total or average of a subset of variables, or a difference variable that is the difference of one variable subtracted from another. This makes short work of summarizing questionnaires or test scores into a total score. If you have pretest and posttest data, the difference variable function allows you to quickly calculate a difference score.
ADVANCED: Contains the statistical hypothesis testing functions of EZAnalyze:
Correlation: Calculates the Pearson correlation coefficient for two variables, which allows you to describe the degree of relationship between those two variables - includes the p-value to ascertain statistical significance. A scatterplot is also automatically generated.
One Sample T-Test: Calculates a T score and P value for the observed difference between an observed mean in your data and a known mean. A bar graph is also automatically generated.
Paired Samples T-Test: Calculates T and P for the observed difference between two "repeated measures" or paired variables. A bar graph is also automatically generated.
Independent Samples T-Test: Calculates T and P for the observed difference between two group means. A bar graph is also automatically generated.
ANOVA: Calculates F and P, and generates an ANOVA table for a single factor between-subjects ANOVA. Also creates a bar graph disaggregating your dependent variable by the factor.
Chi Square: Calculates the chi squared value and P for non-parametric frequency data. Generates a chi squared table reporting observed and expected values.
TO SEE THE OUTPUT OF THESE FUNCTIONS, PLEASE SEE THE "RESULTS REPORT" SECTION OF THIS WEBSITE
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