Data Statistics in 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.
Mostraxe
Create a table with data sampled from another table.
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.
Método de mostraxe
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.
Exemplo
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 |
EstatÃsticas descritivas
Fill a table in the spreadsheet with the main statistical properties of the data set.
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.
The following table displays the results of the descriptive statistics of the sample data above.
Columna |
Columna |
Columna |
|
Media |
41.9090909091 |
59.7 |
44.7 |
Standard Error |
3.5610380138 |
5.3583786934 |
4.7680650629 |
Modo |
47 |
49 |
60 |
MEDIANA |
40 |
64.5 |
43.5 |
Varianza |
139.4909090909 |
287.1222222222 |
227.3444444444 |
Standard Deviation |
11.8106269559 |
16.944681237 |
15.0779456308 |
Kurtosis |
-1.4621677981 |
-0.9415988746 |
1.418052719 |
Skewness |
0.0152409533 |
-0.2226426904 |
-0.9766803373 |
Intervalo |
31 |
51 |
50 |
MÃnimo |
26 |
33 |
12 |
Máximo |
57 |
84 |
62 |
Suma |
461 |
597 |
447 |
Conta |
11 |
10 |
10 |
Análise de varianza (ANOVA)
Produces the analysis of variance (ANOVA) of a given data set
ANOVA is the acronym for ANalysis Of VAriance. This tool produces the analysis of variance of a given data set

For more information on ANOVA, refer to the corresponding Wikipedia article.
Tipo
Select if the analysis is for a single factor or for two factor ANOVA.
Parámetros
Alpha: the level of significance of the test.
Rows per sample: Define how many rows a sample has.
The following table displays the results of the analysis of variance (ANOVA) of the sample data above.
ANOVA - Single Factor |
|||||
Alfa: |
0.05 |
||||
Grupos |
Conta |
Suma |
Media |
Varianza |
|
Columna |
11 |
461 |
41.9090909091 |
139.4909090909 |
|
Columna |
10 |
597 |
59.7 |
287.1222222222 |
|
Columna |
10 |
447 |
44.7 |
227.3444444444 |
|
Source of Variation |
SS |
df |
ms |
F |
P-value |
Entre grupos |
1876.5683284457 |
2 |
938.2841642229 |
4.3604117704 |
0.0224614952 |
Dentro de grupos |
6025.1090909091 |
28 |
215.1824675325 |
||
Total |
7901.6774193548 |
30 |
Correlación
Calcula a correlación entre dous conxuntos de datos numéricos.
O coeficiente de correlación (un valor entre -1 e +1) indica a forza coa que se relacionan dúas variábeis entre si. Pódese empregar a función CORREL ou EstatÃsticas de datos para atopar o coeficiente de correlación entre dúas variábeis.
Un coeficiente de correlación de +1 indica unha correlación positiva perfecta.
Un coeficiente de correlación de -1 indica unha correlación negativa perfecta

For more information on statistical correlation, refer to the corresponding Wikipedia article.
A táboa seguinte mostra os resultados da correlación dos datos de exemplo anteriores.
Correlación |
Columna |
Columna |
Columna |
Columna |
1 |
||
Columna |
-0.4029254917 |
1 |
|
Columna |
-0.2107642836 |
0.2309714048 |
1 |
Covarianza
Calcula a covarianza de dous conxuntos de datos numéricos.
A covarianza é unha medida de canto cambian xuntas dúas variábeis aleatorias.

For more information on statistical covariance, refer to the corresponding Wikipedia article.
A táboa seguinte mostra os resultados da covarianza dos datos de exemplo anteriores.
Covarianza |
Columna |
Columna |
Columna |
Columna |
126.8099173554 |
||
Columna |
-61.4444444444 |
258.41 |
|
Columna |
-32 |
53.11 |
204.61 |
Suavizado exponencial
Resultados en series de datos suavizados
O suavizado exponencial é unha técnica de filtrado que produce resultados suavizados ao ser aplicada a un conxuntos de datos. Emprégase en moitos dominios, como no mercado de valores, na economÃa e en medidas de mostras.

For more information on exponential smoothing, refer to the corresponding Wikipedia article.
Parámetros
Smoothing Factor: A parameter between 0 and 1 that represents the damping factor Alpha in the smoothing equation.
O suavizado resultante aparece abaixo cun factor de suavizado de 0,5:
Alfa: |
|
0.5 |
|
Columna |
Columna |
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 |
Media móbil
Calcula a media móbil dunha serie temporal

For more information on the moving average, refer to the corresponding Wikipedia article.
Parámetros
Intervalo: O número de mostras empregado no cálculo da media móbil.
Resultados da media móbil:
Columna |
Columna |
#N/A |
#N/A |
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/A |
#N/A |
Paired t-test
Calculates the paired t-Test of two data samples.
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.
Datos
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.
Results for paired t-test:
The following table shows the paired t-test for the data series above:
paired t-test |
||
Alfa: |
0.05 |
|
Hypothesized Mean Difference |
0 |
|
Variábel 1 |
Variábel 2 |
|
Media |
16.9230769231 |
20.4615384615 |
Varianza |
125.0769230769 |
94.4358974359 |
Observations |
13 |
13 |
Pearson Correlation |
-0.0617539772 |
|
Observed Mean Difference |
-3.5384615385 |
|
Varianza das diferenzas |
232.9358974359 |
|
df |
12 |
|
t Stat |
-0.8359262137 |
|
P (T<=t) one-tail |
0.2097651442 |
|
t Critical one-tail |
1.7822875556 |
|
P (T<=t) two-tail |
0.4195302884 |
|
t Critical two-tail |
2.1788128297 |
F-test
Calculates the F-Test of two data samples.
A F-test is any statistical test based on the F-distribution under the null hypothesis.

For more information on F-tests, refer to the corresponding Wikipedia article.
Datos
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.
Results for F-Test:
The following table shows the F-Test for the data series above:
Ftest |
||
Alfa: |
0.05 |
|
Variábel 1 |
Variábel 2 |
|
Media |
16.9230769231 |
20.4615384615 |
Varianza |
125.0769230769 |
94.4358974359 |
Observations |
13 |
13 |
df |
12 |
12 |
F |
1.3244637524 |
|
P (F<=f) right-tail |
0.3170614146 |
|
F Critical right-tail |
2.6866371125 |
|
P (F<=f) left-tail |
0.6829385854 |
|
F Critical left-tail |
0.3722125312 |
|
P two-tail |
0.6341228293 |
|
F Critical two-tail |
0.3051313549 |
3.277277094 |
Z-test
Calculates the z-Test of two data samples.

For more information on Z-tests, refer to the corresponding Wikipedia article.
Datos
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.
Results for z-Test:
The following table shows the z-Test for the data series above:
z-test |
||
Alfa: |
0.05 |
|
Hypothesized Mean Difference |
0 |
|
Variábel 1 |
Variábel 2 |
|
Known Variance |
0 |
0 |
Media |
16.9230769231 |
20.4615384615 |
Observations |
13 |
13 |
Observed Mean Difference |
-3.5384615385 |
|
z |
#DIV/0! |
|
P (Z<=z) one-tail |
#DIV/0! |
|
z Critical one-tail |
1.644853627 |
|
P (Z<=z) two-tail |
#DIV/0! |
|
z Critical two-tail |
1.9599639845 |
Chi-square test
Calculates the Chi-square test of a data sample.

For more information on chi-square tests, refer to the corresponding Wikipedia article.
Datos
Input range: The reference of the range of the data series to analyze.
Results to: The reference of the top left cell of the range where the test will be displayed.
Results for Chi-square Test:
Test of Independence (Chi-Square) |
|
Alfa: |
0.05 |
df |
12 |
P-value |
2.32567054678584E-014 |
Test Statistic |
91.6870055842 |
Critical Value |
21.0260698175 |