1. How to do regression and correlation with fx-3650

2. Step 1 Choose REG mode for linear regression Press the buttons [Mode][Mode][2][1] Mode

3. Step 2 Data entry 101003 151005 201010 251011 301014 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] SHIFTCLR DT EXE

4. 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 x2x2

5. Step 3 Finding the correlation coefficient For the correlation coefficient r (0.983) Press SHIFT S-VAR EXE

6. Other useful outputs

7. How to do regression and correlation with fx-911

8. Linear Regression

9. 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]

10. Step 2 Data entry 101003 151005 201010 251011 301014 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

11. 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

12. Correlation

13. 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]

14. Step 2 Data entry 101003 151005 201010 251011 301014 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

15. Step 3 compute r r = [  x 1 x 2 - (  x 1  x 2 )/n]  {[  x 1 2 – (  x 1 ) 2 /n][  x 2 2 – (  x 2 ) 2 /n] For  x 1 x 2 press [RCL][F]  x 1 press [RCL][B]  x 2 press [RCL][E]  x 1 2 press [RCL][A]  x 2 2 press [RCL][D] you should find r = 0.983

16. For Old Calculators….fx-3400p or fx-3600 p Mode: 2 (LR) Clear data: shift, AC Enter data x, then X D; 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

17. 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

18. 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 Ho Support hypothesis and model Retain Ho Refute hypothesis and model Interpretation Don't end here Experiment Critical test of null hypothesis Null Hypothesis Logical opposite to hypothesis Hypothesis Predictions based on model Models Explanations or theories Start here Observations Patterns in space or time