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3. In table 2 below, record the number of corn kernels that are smooth and rough. Table 2: Number of kernels Texture smooth rough Total Number of Kernels 215 35 150 4. Compare your observed and expected results by doing the chi-square test (Table 3). Notes on calculating the chi-square number Obtain your observed values (counted number of smooth kernels, counted number of rough kernels) from Table 2 above. Calculate your expected (e) values based on your predicted phenotypic ratio and using the total number of kernels calculated in Table 2. For example, if your predicted ratio is 1:1 (smooth : rough) and the total number of kernels obtained is 600, your e value for smooth kernels would be 300 (1/2 x 600) and your e value for rough kernels would also be 300. 01.22 (td) The symbol > means the sum of. Therefore, you need to add all the d²/e values to get your chi- square (X²) number. Table 3: Chi-square calculations Observed value (0) Expected value (e) Deviation (o-e) or d Smooth texture Lab 11-8 BIO111: General Biology I Rough Texture

3. In table 2 below, record the number of corn kernels that are smooth and rough. Table 2: Number of kernels Texture smooth rough Total Number of Kernels 215 35 150 4. Compare your observed and expected results by doing the chi-square test (Table 3). Notes on calculating the chi-square number Obtain your observed values (counted number of smooth kernels, counted number of rough kernels) from Table 2 above. Calculate your expected (e) values based on your predicted phenotypic ratio and using the total number of kernels calculated in Table 2. For example, if your predicted ratio is 1:1 (smooth : rough) and the total number of kernels obtained is 600, your e value for smooth kernels would be 300 (1/2 x 600) and your e value for rough kernels would also be 300. 01.22 (td) The symbol > means the sum of. Therefore, you need to add all the d²/e values to get your chi- square (X²) number. Table 3: Chi-square calculations Observed value (0) Expected value (e) Deviation (o-e) or d Smooth texture Lab 11-8 BIO111: General Biology I Rough Texture

Human Anatomy & Physiology (11th Edition)
Human Anatomy & Physiology (11th Edition)
11th Edition
ISBN:9780134580999
Author:Elaine N. Marieb, Katja N. Hoehn
Publisher:Elaine N. Marieb, Katja N. Hoehn
Chapter1: The Human Body: An Orientation
Section: Chapter Questions
Problem 1RQ: The correct sequence of levels forming the structural hierarchy is A. (a) organ, organ system,...
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3. In table 2 below, record the number of corn kernels that are smooth and rough. Table 2: Number of kernels Texture smooth rough Total 4. Compare your observed and expected results by doing the chi-square test (Table 3). Notes on calculating the chi-square number Obtain your observed values (counted number of smooth kernels, counted number of rough kernels) from Table 2 above. Number of Kernels 215 Calculate your expected (e) values based on your predicted phenotypic ratio and using the total number of kernels calculated in Table 2. For example, if your predicted ratio is 1:1 (smooth: rough) and the total number of kernels obtained is 600, your e value for smooth kernels would be 300 (1/2 x 600) and your e value for rough kernels would also be 300. 01.22 (td) The symbol > means the sum of. Therefore, you need to add all the d²/e values to get your chi- square (X2) number. 35 150 ceetb Table 3: Chi-square calculations Observed value (o) Expected value (e) Deviation² (d²) d²/e Deviation (o-e) or di . Smooth texture Lab 11-8 BIO111: General Biology I Chi-square, X²= [d²/e If you have a ratio of 3:1 then to calculate the percentage, you have to add the total sum of the groups and that is your denominator (4) and then each group is the numerator. For example % is 75% and % is 25% which equals 100%. S. Using Table 4, what is your p value? Rough Texture Use your X² number to determine your p (probability) value. Your p value will tell you whether there is a significant difference between your observed and expected values. This will help you to determine whether your hypothesis is supported. If you get a p value greater than 0.05, it means that there is no significant difference between your observed and expected values and therefore your hypothesis is supported.
Transcribed Image Text:3. In table 2 below, record the number of corn kernels that are smooth and rough. Table 2: Number of kernels Texture smooth rough Total 4. Compare your observed and expected results by doing the chi-square test (Table 3). Notes on calculating the chi-square number Obtain your observed values (counted number of smooth kernels, counted number of rough kernels) from Table 2 above. Number of Kernels 215 Calculate your expected (e) values based on your predicted phenotypic ratio and using the total number of kernels calculated in Table 2. For example, if your predicted ratio is 1:1 (smooth: rough) and the total number of kernels obtained is 600, your e value for smooth kernels would be 300 (1/2 x 600) and your e value for rough kernels would also be 300. 01.22 (td) The symbol > means the sum of. Therefore, you need to add all the d²/e values to get your chi- square (X2) number. 35 150 ceetb Table 3: Chi-square calculations Observed value (o) Expected value (e) Deviation² (d²) d²/e Deviation (o-e) or di . Smooth texture Lab 11-8 BIO111: General Biology I Chi-square, X²= [d²/e If you have a ratio of 3:1 then to calculate the percentage, you have to add the total sum of the groups and that is your denominator (4) and then each group is the numerator. For example % is 75% and % is 25% which equals 100%. S. Using Table 4, what is your p value? Rough Texture Use your X² number to determine your p (probability) value. Your p value will tell you whether there is a significant difference between your observed and expected values. This will help you to determine whether your hypothesis is supported. If you get a p value greater than 0.05, it means that there is no significant difference between your observed and expected values and therefore your hypothesis is supported.
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