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.

Lai piekļūtu šai komandai...

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.

Piezīmes ikona

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.

Lai piekļūtu šai komandai...

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.

Piezīmes ikona

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

Lai piekļūtu šai komandai...

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

Piezīmes ikona

For more information on ANOVA, 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.

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.

Lai piekļūtu šai komandai...

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

Piezīmes ikona

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.

Lai piekļūtu šai komandai...

Choose Data - Statistics - Covariance


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

Piezīmes ikona

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

Lai piekļūtu šai komandai...

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.

Piezīmes ikona

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

Lai piekļūtu šai komandai...

Choose Data - Statistics - Moving Average


Piezīmes ikona

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.

Lai piekļūtu šai komandai...

Choose Data - Statistics - Paired t-test


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

Piezīmes ikona

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.

Lai piekļūtu šai komandai...

Choose Data - Statistics - F-test


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

Piezīmes ikona

For more information on F-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 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.

Lai piekļūtu šai komandai...

Choose Data - Statistics - Z-test


Piezīmes ikona

For more information on Z-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 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


Hī kvadrāta tests

Calculates the Chi-square test of a data sample.

Lai piekļūtu šai komandai...

Choose Data - Statistics - Chi-square Test


Piezīmes ikona

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


Rezultāti Hī kvadrāta testam:

Test of Independence (Chi-Square)

Alfa

0.05

df

12

P-vērtība

2.32567054678584E-014

Test Statistic

91.6870055842

Kritiskā vērtība

21.0260698175


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