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Once we have a x value we need to determine if it is statistically significant. This is accomplished using a x table (see table below). The values inside the table represent calculated x² values. Before

Once we have a x value we need to determine if it is statistically significant. This is accomplished using a x table (see table below). The values inside the table represent calculated x² values. Before

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Once we have a x? value we need to determine if it is statistically significant. This is accomplished using a x table (see table below). The values inside the table represent calculated x values. Before For Educational Purposes Only SLSU-TO/NCMatondo 10 we can either accept or reject the null hypothesis, we need to determine our alpha (P-value) and degrees of freedom (df). P-values can be interpreted in multiple ways. For example, suppose we obtained a x? of 0.016 with 1 df. Based on the table, random chance alone would produce a x² value greater than 0.016 over 90% of the time (see bold square in table). In most statistical hypothesis testing we adopt an alpha (P-value) of 0.05 or 5%. Examining the table, with 1 df we would need a x? > 3.841 (known as the critical value) in order to reject the null hypothesis of no significant difference between observed and expected values. Degrees of freedom is obtained by subtracting 1 from the total number of categories (n – 1). For example, in our cards example df = 3. Chi-Square Table Table S-2 Critical Values of thex2 Diseribution 00a016 046S 2706 3041 1.36 405 5991 7.378 9210 10597 2 0072 0216 0504 2366 6251 7015 9349 11345 120e 3 a207 044 1064 357 7.79 94 11.143 13277 140 4 D412 0831 1810 41 9236 11.070 12832 15.06 16.750 5 DE76 1237 2.204 OP09 1490 2030 1344 2.100 3490 1.735 2.700 4,168 5.348 10645 12592 14449 16812 18548 e 6.346 12017 14067 16013 10475 202707 7.44 12 15s07 1755 2000 21SE 8.343 144 16.919 19023 21 23se 9 9342 157 10.307 20403 2209 25100 10 10 2156 3247 406 2.603 3016 5570 1041 17275 19675 21.920 24725 26757 11 074 4404 6.304 11340 18549 21.024 23.337 2217 2800 12 11 12 13 35e5 S009 7012 12340 19012 22362 24.736 2760 29019 19 4.075 S629 7.790 13339 21064 236s 26.119 29.141 31319 14 4.601 6242 8547 14339 22.307 24996 27488 30578 32801 15 14 Working in groups of two, perform six x² analyses using the data from the tables above. What can you conclude from your analysis?
Transcribed Image Text:Once we have a x? value we need to determine if it is statistically significant. This is accomplished using a x table (see table below). The values inside the table represent calculated x values. Before For Educational Purposes Only SLSU-TO/NCMatondo 10 we can either accept or reject the null hypothesis, we need to determine our alpha (P-value) and degrees of freedom (df). P-values can be interpreted in multiple ways. For example, suppose we obtained a x? of 0.016 with 1 df. Based on the table, random chance alone would produce a x² value greater than 0.016 over 90% of the time (see bold square in table). In most statistical hypothesis testing we adopt an alpha (P-value) of 0.05 or 5%. Examining the table, with 1 df we would need a x? > 3.841 (known as the critical value) in order to reject the null hypothesis of no significant difference between observed and expected values. Degrees of freedom is obtained by subtracting 1 from the total number of categories (n – 1). For example, in our cards example df = 3. Chi-Square Table Table S-2 Critical Values of thex2 Diseribution 00a016 046S 2706 3041 1.36 405 5991 7.378 9210 10597 2 0072 0216 0504 2366 6251 7015 9349 11345 120e 3 a207 044 1064 357 7.79 94 11.143 13277 140 4 D412 0831 1810 41 9236 11.070 12832 15.06 16.750 5 DE76 1237 2.204 OP09 1490 2030 1344 2.100 3490 1.735 2.700 4,168 5.348 10645 12592 14449 16812 18548 e 6.346 12017 14067 16013 10475 202707 7.44 12 15s07 1755 2000 21SE 8.343 144 16.919 19023 21 23se 9 9342 157 10.307 20403 2209 25100 10 10 2156 3247 406 2.603 3016 5570 1041 17275 19675 21.920 24725 26757 11 074 4404 6.304 11340 18549 21.024 23.337 2217 2800 12 11 12 13 35e5 S009 7012 12340 19012 22362 24.736 2760 29019 19 4.075 S629 7.790 13339 21064 236s 26.119 29.141 31319 14 4.601 6242 8547 14339 22.307 24996 27488 30578 32801 15 14 Working in groups of two, perform six x² analyses using the data from the tables above. What can you conclude from your analysis?
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