Questions: PHENOTYPES, OBSERVE, EXPECTED, O-E, (O-E)^2 Dark Brown eyes, 125, , , Light brown cyes, 78, , , Light brown eyes, 87, , , White cyes, 25, , , TOTAL, , , ,

PHENOTYPES, OBSERVE, EXPECTED, O-E, (O-E)^2
Dark Brown eyes, 125, , , 
Light brown cyes, 78, , , 
Light brown eyes, 87, , , 
White cyes, 25, , , 
TOTAL, , , ,
Transcript text: \begin{tabular}{|l|l|l|l|l|} \hline PHENOTYPES & OBSERVE & EXPECTED & O-E & $(\mathrm{O}-\mathrm{E})^{2}$ \\ \hline Dark Brown eyes & 125 & & & \\ \hline Light brown cyes & 78 & & & \\ \hline Light brown eyes & 87 & & & \\ \hline White cyes & 25 & & & \\ \hline TOTAL & & & & \\ \hline \end{tabular}
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Solution

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Solution Steps

Step 1: Calculate Expected Frequencies

The expected frequencies for each phenotype, assuming equal distribution, are calculated as follows:

E=Nk=3154=78.75 E = \frac{N}{k} = \frac{315}{4} = 78.75

where NN is the total number of observations (315) and kk is the number of phenotypes (4). Thus, the expected frequencies are:

E=[78.75,78.75,78.75,78.75] E = [78.75, 78.75, 78.75, 78.75]

Step 2: Perform Chi-Square Test

The Chi-Square test statistic (χ2\chi^2) is calculated using the formula:

χ2=i(OiEi)2Ei \chi^2 = \sum_i \frac{(O_i - E_i)^2}{E_i}

Substituting the observed (OO) and expected (EE) values:

χ2=(12578.75)278.75+(7878.75)278.75+(8778.75)278.75+(2578.75)278.75 \chi^2 = \frac{(125 - 78.75)^2}{78.75} + \frac{(78 - 78.75)^2}{78.75} + \frac{(87 - 78.75)^2}{78.75} + \frac{(25 - 78.75)^2}{78.75}

Calculating this gives:

χ2=64.7206 \chi^2 = 64.7206

Step 3: Determine Degrees of Freedom and Critical Value

The degrees of freedom (dfdf) for this test is given by:

df=k1=41=3 df = k - 1 = 4 - 1 = 3

Using a significance level of α=0.05\alpha = 0.05, the critical value for the Chi-Square distribution with 3 degrees of freedom is:

χ2(0.95,3)=7.8147 \chi^2(0.95, 3) = 7.8147

Step 4: Calculate P-Value

The p-value associated with the calculated Chi-Square statistic is:

P=P(χ2>64.7206)=0.0 P = P(\chi^2 > 64.7206) = 0.0

Final Answer

The results of the Chi-Square Goodness-of-Fit Test are summarized as follows:

  • Chi-Square Statistic: χ2=64.7206 \chi^2 = 64.7206
  • Degrees of Freedom: df=3 df = 3
  • P-Value: P=0.0 P = 0.0
  • Critical Value: χ2(0.95,3)=7.8147 \chi^2(0.95, 3) = 7.8147

Since the Chi-Square statistic exceeds the critical value and the p-value is less than α\alpha, we reject the null hypothesis.

Reject the null hypothesis \boxed{\text{Reject the null hypothesis}}

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