Statistics Calculator

Statistics Calculator

The statistics calculator computes statistics for numerical variables grouped by combinations of categorical variables. If the data contains only categorical variables, it computes the frequency and percentage of each combination. If the data contains only numerical variables, it computes statistics for each numerical variable.

How to use the statistics calculator

Statistics calculator with optional Excel input. Computes statistics such as minimum, maximum, sum, count, standard deviation, quartiles, IQR, and skewness. Handles both numerical and categorical data. Insert one or more columns, and the statistics calculator processes each separately.

How to enter data?

• Enter raw data directly - usually you have the raw data.
  a. Enter the name of the group.
  b. Enter the raw data separated by 'comma', 'space', or 'enter'. (*you may copy only the data from excel).
• Enter raw data from excel

  Enter the header on the first row.

  1. Copy Paste
     
     • Copy the raw data with the header from Excel or Google sheets, or any tool that separates data with tab and line feed. copy the entire block, include the header .
     • Paste the data in the input field.
  2. Import data from an Excel or CSV file
     When you select an Excel file, the calculator will automatically load the first sheet and display it in the input field. You can choose either an Excel file (.xlsx or .xls) or a CSV file (.csv).
     To upload your file, use one of the following methods:
     • Browse and select – Click the 'Browse' button and choose a file from your computer.
       
     • Drag and drop – Drag your file and drop it into the 'Drop your .xlsx, .xls, or .csv file here!' area.
     Once the file is uploaded, the statistics calculator will display the data from the first sheet in the input field.
     Now, the 'Select sheet' dropdown will be populated with the names of your sheets, and you can choose any sheet.
  3. Filter Data
     When using the 'Enter data from Excel' option, you can filter the data by clicking the following icon above the header:
     You may select one or more values from the dropdown. Please note that the filter will include any value that contains the values you choose.

Numerical data

Quantitative data, continuous variable or ordinal variable

Categorical data

Qualitative data, categorical variable

Choose the statistics that you want to present

Numerical and Categorical Data

1. Count (n) - number of observations, the count of valid values, excluding empty cells or non-numerical cells for quantitative data
2. Percentage - the percentage of valid values, excluding empty cells or non-numerical cells for quantitative data
3. Missing values - number of missing values - the count of empty cells or non-numerical cells for quantitative data.

Numerical data

1. Min - minimum, the lowest value.
2. Max - maximum, the highest value.
3. Range - the distance between the minimum and the maximum.
4. Mean (x̄) - the average.
5. Mean CI - the confidence interval of the mean.
6. Sum - the cumulative total of all the values.
7. Standard Deviation (S), the sample standard deviation. Use it when you have only a sample data.
8. Variance (S²) - the sample variance.
9. Standard Deviation (σ), the population standard deviation, use it when you have the entire population data.
10. SD CI - the confidence interval of the standard deviation.
11. Variance (σ²) - the population variance, use it when you have the entire population data.
12. Sum of squares - refers to the sum of the square distances of all the values from the mean.
13. Q1- quartile 1, the 25th percentile.
14. Median- quartile 2, the 50th percentile.
15. Q3- quartile 3, the 75th percentile.
16. IQR - InterQuartile Range - the different between Quartile 1 and Quartile 3.
17. Skewness - the symmetrical level of the probability distribution
18. Skewness shape - text description of the skewness and the p-value of the test for a difference from normal skewness.
19. Excess kurtosis - the kurtosis difference from the normal distribution, the Kurtosis measured the level of the tails.
20. Tails shape - text description of the kurtosis and the p-value of the test for a difference from normal kurtosis.
21. Outliers - using the Tukey's Fences
22. SW p-value - Shapiro Wilk test for normality. For more details, refer the Kolmogorov-Smirnov test
23. KS p-value - Kolmogorov-Smirnov test for normality based on the sample parameters (Lilliefors test). For other options, refer to the Kolmogorov-Smirnov test

Options

1. Outliers: extreme values. relevant only if you entered raw data.
   included - the calculator will calculate the outliers but will include them in the calculation.
   Excluded - The calculator will exclude the outliers before calculating the average and the standard deviation.
2. Format the numbers - the thousand separator and the decimal point.
3. Decimal Format - how to round the results?
   Smart When a resulting value is larger than one, the tool rounds it, but when a resulting value is less than one the tool displays the significant figures. Decimal places - the number of decimal places, except for the 'Count' and 'Num of Missing Value'.
4. Histogram - create a histogram for the data.
5. Boxplot - create a boxplot for the data.
6. Standardized - create table with standardized data for each variable. The standardized transformation is a way to compare data with different units of measure; it translates each value into a z-score.
   $z = \frac{x - \mu }{\sigma }$
7. Excel Pagination Display - the number of rows displayed per tab in the 'Enter data from Excel' option. This option displays the spreadsheet across multiple tabs.

Options

Cleaning the data

The calculator cleans the data but not the header, as follows:

1. Remove non-numerical characters - the calculator keeps only the following characters:
   numbers ('0'-'9'), minus ('-'), decimal point ('.'), and brackets ('(', ')').
2. Convert numbers in brackets to negative numbers.
3. Convert standalone minus signs to 0.

Examples

Should you exclude outliers?

It is important to exercise caution before excluding outliers from any calculation, as they may contain valuable information. However, excluding outliers from a histogram may significantly improve its visualization, even if the outliers are valid observations. If you choose to exclude outliers, the histogram maker will generate the chart without them. This method can create a more practical histogram that better represents the distribution of the majority of the data points.