How to do regression and correlation with fx-3650

Step 1 Choose REG mode

for linear regression

Press the buttons

[Mode][Mode][2][1]

Mode

Step 2 Data entry

10 1003

15 1005

20 1010

25 1011

30 1014

For entering this dataset

clear all data

[SHIFT][CLR][1][EXE]

data entry

10[,]1003[DT]15[,]1005

[DT]20[,]1010[DT]25[,]

1011[DT]30[,]1014[DT]

SHIFT CLR

DT

EXE

Step 3 Finding the regression equation

For the equation y=A+Bx

For A (997.4)

Press

For B (0.56)

Press

For regression coeff. (0.966)

Press

SHIFT

S-VAR

EXE

x2

Step 3 Finding the correlationcoefficient

For the correlationcoefficient r (0.983)

Press

SHIFT

S-VAR

EXE

Other useful outputs

How to do regression and correlation with

fx-911

Linear Regression

Step 1 Choose REG mode

Use Mode 3 (REG)

You are offered 3 choices

choose linear regression

option (1)

Press the buttons

[Mode][3][1]

Step 2 Data entry

10 1003

15 1005

20 1010

25 1011

30 1014

For entering this dataset

clear all data

[SHIFT][Sci][=]

data entry

10[,]1003[DT]15[,]1005

[DT]20[,]1010[DT]25[,]

1011[DT]30[,]1014[DT]

SHIFT

Sci

DT

Step 3 Finding the regression equation

For the equation y=A+Bx

For A (997.4)

Press [SHIFT][A][=]

For B (0.56)

Press [SHIFT][B][=]

For regression coeff. (0.966)

Press [SHIFT][r][=]

SHIFT

A

r

B

Correlation

Step 1 Choose REG mode

Use Mode 3 (REG)

You are offered 3 choices

choose linear regression

option (1)

Press the buttons

[Mode][3][1]

Step 2 Data entry

10 1003

15 1005

20 1010

25 1011

30 1014

For entering this dataset

clear all data

[SHIFT][Sci][=]

data entry

10[,]1003[DT]15[,]1005

[DT]20[,]1010[DT]25[,]

1011[DT]30[,]1014[DT]

SHIFT

Sci

DT

Step 3 compute r

r = [x1x2 - (x1 x2)/n]

{[x12 – (x1)2/n][x2

2 – (x2)2/n]

For

x1x2 press [RCL][F]

x1 press [RCL][B]

x2 press [RCL][E]

x12 press [RCL][A]

x22 press [RCL][D]

you should find r = 0.983

For Old Calculators….fx-3400p or fx-3600 p

• Mode: 2 (LR)

• Clear data: shift, AC• Enter data x, then XD; Enter data y, then

DATA• Check N for entered dataset: Kout, n (3)• y = A + Bx: shift, A (7) = A; shift, B (8) = B;

shift, r (9) = r coefficient of correlation

Experimental Design and Statistics

1. Setting questions into statistical questions

2. Setting hypotheses (i.e. expected/theoretical one)

3. Setting statistical null hypotheses

4. Statistical consideration (treatment groups, sample size, replicates, confounding factors, controls etc.)

5. Experimental design

6. Data collection

7. Data analysis

Generalized scheme of logical components of a research programme (Underwood 1997)

Weapon size versus body size as a predictor of

winning fights

Carcinus maenas

Reference: Sneddon et al. 1997, in Behav. Ecol. Sociobiol. 41: 237 - 242

Weapon size versus body size as a predictor of

winning fights

Carcinus maenas

Reference: Sneddon et al. 1997, in Behav. Ecol. Sociobiol. 41: 237 - 242

Reject HoSupporthypothesisand model

Retain HoRefutehypothesisand model

InterpretationDon't end here

ExperimentCritical test of null hypothesis

Null HypothesisLogical opposite to hypothesis

HypothesisPredictions based on model

ModelsExplanations or theories

Start hereObservations

Patterns in space or time