# Datu statistika iekš Calc

Use the data statistics in Calc to perform complex data analysis

To work on a complex statistical or engineering analysis, you can save steps and time by using Calc Data Statistics. You provide the data and parameters for each analysis, and the set of tools uses the appropriate statistical or engineering functions to calculate and display the results in an output table.

## Iztvērums

Create a table with data sampled from another table.

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Choose Data - Statistics - Sampling

Sampling allows you to pick data from a source table to fill a target table. The sampling can be random or in a periodic basis.

Sampling is done row-wise. That means, the sampled data will pick the whole line of the source table and copy into a line of the target table.

### Dati

Input Range: The reference of the range of the data to analyze.

Results to: The reference of the top left cell of the range where the results will be displayed.

### Izlases ieguves metode

Random: Picks exactly Sample Size lines of the source table in a random way.

Sample size: Number of lines sampled from the source table.

Periodic: Picks lines in a pace defined by Period.

Period: the number of lines to skip periodically when sampling.

#### Example

The following data will be used as example of source data table for sampling:

 A B C 1 11 21 31 2 12 22 32 3 13 23 33 4 14 24 34 5 15 25 35 6 16 26 36 7 17 27 37 8 18 28 38 9 19 29 39

Sampling with a period of 2 will result in the following table:

 12 22 32 14 24 34 16 26 36 18 28 38

## Aprakstošā statistika

Fill a table in the spreadsheet with the main statistical properties of the data set.

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Choose Data - Statistics - Descriptive Statistics

The Descriptive Statistics analysis tool generates a report of univariate statistics for data in the input range, providing information about the central tendency and variability of your data.

For more information on descriptive statistics, refer to the corresponding Wikipedia article.

### Dati

Input Range: The reference of the range of the data to analyze.

Results to: The reference of the top left cell of the range where the results will be displayed.

### Grupēts pēc

Select whether the input data has columns or rows layout.

#### Example

Sekojošie dati tiks lietoti kā piemērs

 A B C 1 Matemātika Fizika Bioloģija 2 47 67 33 3 36 68 42 4 40 65 44 5 39 64 60 6 38 43 7 47 84 62 8 29 80 51 9 27 49 40 10 57 49 12 11 56 33 60 12 57 13 26

The following table displays the results of the descriptive statistics of the sample data above.

 Kolonna 1 Kolonna 2 Kolonna 3 Vidējais 41.9090909091 59.7 44.7 Standartkļūda 3.5610380138 5.3583786934 4.7680650629 Režīms 47 49 60 Mediāna 40 64.5 43.5 Dispersija 139.4909090909 287.1222222222 227.3444444444 Standartnovirze 11.8106269559 16.944681237 15.0779456308 Ekscesa koeficients -1.4621677981 -0.9415988746 1.418052719 Asimetrija 0.0152409533 -0.2226426904 -0.9766803373 Diapazons 31 51 50 Minimums 26 33 12 Maksimums 57 84 62 Summa 461 597 447 Skaits 11 10 10

## Dispersijas analīze (ANOVA)

Produces the analysis of variance (ANOVA) of a given data set

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Choose Data - Statistics - Analysis of Variance (ANOVA)

ANOVA is the acronym for ANalysis Of VAriance. This tool produces the analysis of variance of a given data set

### Dati

Input Range: The reference of the range of the data to analyze.

Results to: The reference of the top left cell of the range where the results will be displayed.

### Grupēts pēc

Select whether the input data has columns or rows layout.

### Tips

Select if the analysis is for a single factor or for two factor ANOVA.

### Parametri

Alpha: the level of significance of the test.

Rows per sample: Define how many rows a sample has.

#### Example

Sekojošie dati tiks lietoti kā piemērs

 A B C 1 Matemātika Fizika Bioloģija 2 47 67 33 3 36 68 42 4 40 65 44 5 39 64 60 6 38 43 7 47 84 62 8 29 80 51 9 27 49 40 10 57 49 12 11 56 33 60 12 57 13 26

The following table displays the results of the analysis of variance (ANOVA) of the sample data above.

 ANOVA - viens koeficients Alfa 0.05 Grupas Skaits Summa Vidējais Dispersija Kolonna 1 11 461 41.9090909091 139.4909090909 Kolonna 2 10 597 59.7 287.1222222222 Kolonna 3 10 447 44.7 227.3444444444 Avota variācija SS df MS F P-vērtība F-critical Starp grupām 1876.5683284457 2 938.2841642229 4.3604117704 0.0224614952 3.340385558 Grupās 6025.1090909091 28 215.1824675325 Pavisam 7901.6774193548 30

## Korelācija

Calculates the correlation of two sets of numeric data.

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Choose Data - Statistics - Correlation

The correlation coefficient (a value between -1 and +1) means how strongly two variables are related to each other. You can use the CORREL function or the Data Statistics to find the correlation coefficient between two variables.

A correlation coefficient of +1 indicates a perfect positive correlation.

A correlation coefficient of -1 indicates a perfect negative correlation

For more information on statistical correlation, refer to the corresponding Wikipedia article.

### Dati

Input Range: The reference of the range of the data to analyze.

Results to: The reference of the top left cell of the range where the results will be displayed.

### Grupēts pēc

Select whether the input data has columns or rows layout.

#### Example

Sekojošie dati tiks lietoti kā piemērs

 A B C 1 Matemātika Fizika Bioloģija 2 47 67 33 3 36 68 42 4 40 65 44 5 39 64 60 6 38 43 7 47 84 62 8 29 80 51 9 27 49 40 10 57 49 12 11 56 33 60 12 57 13 26

The following table displays the results of the correlation of the sample data above.

 Korelācijas Kolonna 1 Kolonna 2 Kolonna 3 Kolonna 1 1 Kolonna 2 -0.4029254917 1 Kolonna 3 -0.2107642836 0.2309714048 1

## Kovariācija

Calculates the covariance of two sets of numeric data.

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Choose Data - Statistics - Covariance

The covariance is a measure of how much two random variables change together.

For more information on statistical covariance, refer to the corresponding Wikipedia article.

### Dati

Input Range: The reference of the range of the data to analyze.

Results to: The reference of the top left cell of the range where the results will be displayed.

### Grupēts pēc

Select whether the input data has columns or rows layout.

#### Example

Sekojošie dati tiks lietoti kā piemērs

 A B C 1 Matemātika Fizika Bioloģija 2 47 67 33 3 36 68 42 4 40 65 44 5 39 64 60 6 38 43 7 47 84 62 8 29 80 51 9 27 49 40 10 57 49 12 11 56 33 60 12 57 13 26

The following table displays the results of the covariance of the sample data above.

 Kovariācijas Kolonna 1 Kolonna 2 Kolonna 3 Kolonna 1 126.8099173554 Kolonna 2 -61.4444444444 258.41 Kolonna 3 -32 53.11 204.61

## Eksponenciālā gludināšana

Results in a smoothed data series

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Choose Data - Statistics - Exponential Smoothing

Exponential smoothing is a filtering technique that when applied to a data set, produces smoothed results. It is employed in many domains such as stock market, economics and in sampled measurements.

For more information on exponential smoothing, refer to the corresponding Wikipedia article.

### Dati

Input Range: The reference of the range of the data to analyze.

Results to: The reference of the top left cell of the range where the results will be displayed.

### Grupēts pēc

Select whether the input data has columns or rows layout.

### Parametri

Smoothing Factor: A parameter between 0 and 1 that represents the damping factor Alpha in the smoothing equation.

#### Example

The following table has two time series, one representing an impulse function at time t=0 and the other an impulse function at time t=2.

 A B 1 1 0 2 0 0 3 0 1 4 0 0 5 0 0 6 0 0 7 0 0 8 0 0 9 0 0 10 0 0 11 0 0 12 0 0 13 0 0

The resulting smoothing is below with smoothing factor as 0.5:

 Alfa 0.5 Kolonna 1 Kolonna 2 1 0 1 0 0.5 0 0.25 0.5 0.125 0.25 0.0625 0.125 0.03125 0.0625 0.015625 0.03125 0.0078125 0.015625 0.00390625 0.0078125 0.001953125 0.00390625 0.0009765625 0.001953125 0.0004882813 0.0009765625 0.0002441406 0.0004882813

## Kustīgais vidējais

Calculates the moving average of a time series

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Choose Data - Statistics - Moving Average

For more information on the moving average, refer to the corresponding Wikipedia article.

### Dati

Input Range: The reference of the range of the data to analyze.

Results to: The reference of the top left cell of the range where the results will be displayed.

### Grupēts pēc

Select whether the input data has columns or rows layout.

### Parametri

Interval: The number of samples used in the moving average calculation.

#### Example

The following table has two time series, one representing an impulse function at time t=0 and the other an impulse function at time t=2.

 A B 1 1 0 2 0 0 3 0 1 4 0 0 5 0 0 6 0 0 7 0 0 8 0 0 9 0 0 10 0 0 11 0 0 12 0 0 13 0 0

### Slīdošā vidējā rezultāti:

 Kolonna 1 Kolonna 2 #N/P #N/P 0.3333333333 0.3333333333 0 0.3333333333 0 0.3333333333 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 #N/P #N/P

## Paired t-test

Calculates the paired t-Test of two data samples.

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Choose Data - Statistics - Paired t-test

A paired t-test is any statistical hypothesis test that follows a Student's t distribution.

For more information on paired t-tests, refer to the corresponding Wikipedia article.

### Dati

Variable 1 range: The reference of the range of the first data series to analyze.

Variable 2 range: The reference of the range of the second data series to analyze.

Results to: The reference of the top left cell of the range where the test will be displayed.

### Grupēts pēc

Select whether the input data has columns or rows layout.

#### Example

Sekojošai tabulai ir divas datu kopas.

 A B 1 28 19 2 26 13 3 31 12 4 23 5 5 20 34 6 27 31 7 28 31 8 14 12 9 4 24 10 0 23 11 2 19 12 8 10 13 9 33

### Results for paired t-test:

The following table shows the paired t-test for the data series above:

 paired t-test Alfa 0.05 Minētā vidējā starpība 0 Mainīgais 1 Mainīgais 2 Vidējais 16.9230769231 20.4615384615 Dispersija 125.0769230769 94.4358974359 Novērojumi 13 13 Pīrsona korelācija -0.0617539772 Novērotā vidējā starpība -3.5384615385 Starpību variācija 232.9358974359 df 12 t Stat -0.8359262137 P (T<=t) vienpusējs 0.2097651442 t kritiskais vienpusējs 1.7822875556 P (T<=t) divpusējs 0.4195302884 t kritiskais divpusējs 2.1788128297

## F-tests

Calculates the F-Test of two data samples.

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Choose Data - Statistics - F-test

A F-test is any statistical test based on the F-distribution under the null hypothesis.

### Dati

Variable 1 range: The reference of the range of the first data series to analyze.

Variable 2 range: The reference of the range of the second data series to analyze.

Results to: The reference of the top left cell of the range where the test will be displayed.

### Grupēts pēc

Select whether the input data has columns or rows layout.

#### Example

Sekojošai tabulai ir divas datu kopas.

 A B 1 28 19 2 26 13 3 31 12 4 23 5 5 20 34 6 27 31 7 28 31 8 14 12 9 4 24 10 0 23 11 2 19 12 8 10 13 9 33

### Results for F-Test:

The following table shows the F-Test for the data series above:

 F-tests Alfa 0.05 Mainīgais 1 Mainīgais 2 Vidējais 16.9230769231 20.4615384615 Dispersija 125.0769230769 94.4358974359 Novērojumi 13 13 df 12 12 F 1.3244637524 P (F<=f) labā-aste 0.3170614146 F kritiskā labā puse 2.6866371125 P (F<=f) kreisā puse 0.6829385854 F kritiskā kreisā puse 0.3722125312 P divpusējs 0.6341228293 F kritiskais divpusējs 0.3051313549 3.277277094

## Z-tests

Calculates the z-Test of two data samples.

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Choose Data - Statistics - Z-test

### Dati

Variable 1 range: The reference of the range of the first data series to analyze.

Variable 2 range: The reference of the range of the second data series to analyze.

Results to: The reference of the top left cell of the range where the test will be displayed.

### Grupēts pēc

Select whether the input data has columns or rows layout.

#### Example

Sekojošai tabulai ir divas datu kopas.

 A B 1 28 19 2 26 13 3 31 12 4 23 5 5 20 34 6 27 31 7 28 31 8 14 12 9 4 24 10 0 23 11 2 19 12 8 10 13 9 33

### Results for z-Test:

The following table shows the z-Test for the data series above:

 z-tests Alfa 0.05 Minētā vidējā starpība 0 Mainīgais 1 Mainīgais 2 Zināmā dispersija 0 0 Vidējais 16.9230769231 20.4615384615 Novērojumi 13 13 Novērotā vidējā starpība -3.5384615385 z #DIV/0! P (Z<=z) vienpusējai alternatīvai #DIV/0! z kritiskā vērtība vienpusējai alternatīvai 1.644853627 P (Z<=z) divpusējai alternatīvai #DIV/0! z kritiskā vērtība divpusējai alternatīvai 1.9599639845

Calculates the Chi-square test of a data sample.

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Choose Data - Statistics - Chi-square Test

For more information on chi-square tests, refer to the corresponding Wikipedia article.

### Dati

Input Range: The reference of the range of the data to analyze.

Results to: The reference of the top left cell of the range where the results will be displayed.

### Grupēts pēc

Select whether the input data has columns or rows layout.

#### Example

Sekojošai tabulai ir divas datu kopas.

 A B 1 28 19 2 26 13 3 31 12 4 23 5 5 20 34 6 27 31 7 28 31 8 14 12 9 4 24 10 0 23 11 2 19 12 8 10 13 9 33