Casio ClassPad II fx-CP400 - Manual (Page 240)

Chapter 13: Spreadsheet Application 240
Linear Regression t Test
In a spreadsheet, input paired-variable data (page 237 (c) or (d)) as test data.
1301 To perform a Linear Regression t Test on the paired-variable data
shown in the nearby screenshot
χ
2 Test
For test data, input data of at least one row and two columns (observed matrix) into the spreadsheet. You can
see an actual example (
0704 ) of how this is done using the Statistics application in Chapter 7 of this manual.
χ
2 GOF Test
For test data, input two lists (observed list and expected list) into the spreadsheet. This is equivalent to inputting
two rows of data of
n lines. You can see an actual example ( 0705 ) of how this is done using the Statistics
application in Chapter 7 of this manual.
One-Way ANOVA
For test data, input data (Factor A) into the spreadsheet that is n rows
× 2 columns up to n × 6 columns. You
can see an actual example ( 0706 ) of how this is done using the Statistics application in Chapter 7 of this
manual.
Two-Way ANOVA
When (Factor A count) × (Factor B count) = m , prepare test data that is n rows ×
m columns. For example, when there are Factor A items and one Factor B
items, input six columns of data into the spreadsheet. For example, select
A1:F3 on the spreadsheet and run the wizard. This will automatically assign
the cell references shown below to each factor.
Factor B1 Factor B2 Factor B3
Factor A1 A1:A3 B1:B3 C1:C3
Factor A2 D1:D3 E1:E3 F1:F3
1302 To perform the same calculation as Statistics application example 0707 using the Spreadsheet
application
Distribution Calculations
For details about the different types of distribution calculations, see “Distributions” (page 145).
u To perform a distribution calculation and paste the results into the spreadsheet
1. Enter the single-variable or paired-variable data into the spreadsheet, and then select the range of cells
where it is located.
• The following shows the types of data that correspond to each type of distribution calculation, and the
variables that will be assigned the range of selected data.
Distribution Type Data Variable Assignment
Probability Density Single-variable x
Cumulative Distribution Paired-variable Lower, Upper
Inverse Cumulative Distribution Single-variable prob