You perform a chi-square test to compare observed and expected values and obtain a chi-square value of 9.4 with 3 degrees of freedom. What do you conclude? it is not likely that the difference between observed and expected values is due to random chance, since p>0.05 it is impossible to conclude anything from this information it is likely that the difference between observed and expected values is due to random chance, since p>0.05 it is likely that the difference between observed and expected values is due to random chance, since p<0.05 the experiment was done incorrectly and must be repeated it is not likely that the difference between observed and expected values is due to random chance, since p<0.05

You perform a chi-square test to compare observed and expected values and obtain a chi-square value of 9.4 with 3 degrees of freedom. What do you conclude? it is not likely that the difference between observed and expected values is due to random chance, since p>0.05 it is impossible to conclude anything from this information it is likely that the difference between observed and expected values is due to random chance, since p>0.05 it is likely that the difference between observed and expected values is due to random chance, since p<0.05 the experiment was done incorrectly and must be repeated it is not likely that the difference between observed and expected values is due to random chance, since p<0.05

Human Heredity: Principles and Issues (MindTap Course List)

11th Edition

ISBN:9781305251052

Author:Michael Cummings

Publisher:Michael Cummings

Chapter3: Transmission Of Genes From Generation To Generation

Section3.7: Mendelian Inheritance In Humans

Problem 2EG: For most cases, a p value of 0.05 is used to determine whether results fit expected values. Is this...

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If the chi-square value is 0 under the degree of freedom 1. What could be the interpretation and does it fit in the population of Hardy-Weinberg equilibrium?
Assume that a Chi-square test was conducted to test the goodness of fit to a 3:1 ratio and that a Chi-square value of 2.62 was obtained (Table value is equal to 3.84). Should the null hypothesis be accepted? How many degrees of freedom would be associated with this test of significance?
Which is the correct equation for the chisquare statistic? Group of answer choices a)x^2 = [(observed-expected)^2]/expected b)x^2 = sum[((observed-expected)^2)/observed] c)x^2 = sum[((observed-expected)^2)/expected] d)x^2 = sum[(observed-expected)/expected] What is a "p-value"? Group of answer choices a)the threshold at which you will reject the null hypothesis b)the probability of the null hypothesis being false c)the percentage of days you are sick during the year d)the probability of the null hypothesis being true
Which is the correct equation for the chisquare statistic? Group of answer choices a)x^2 = [(observed-expected)^2]/expected b)x^2 = sum[((observed-expected)^2)/observed] c)x^2 = sum[((observed-expected)^2)/expected] d)x^2 = sum[(observed-expected)/expected] What is a "p-value"? Group of answer choices a)the threshold at which you will reject the null hypothesis b)the probability of the null hypothesis being false c) the percentage of days you are sick during the year d) the probability of the null hypothesis being true
page - Columbus State Uni X content/2622738/viewContent/50155728/View + Calculating the Value of Chi-Square Once you've defined the null hypothesis (and know what you're testing!), you can finally calculate the chi-square value based on your observed data and the expected distribution. There are many statistical software packages and free web-based applications that will automate the calculation for you, but it's important to understand the calculation to understand the meaning of the calculated value. Here, we'll walk through it using a calculation table. This is Mendel's historic data for the F2 generation of monohybrid cross for flower color. Recall that he expected to see in the F2 generation a ratio of 3 purple : 1 white. Chi-square calculation for data from a monohybrid cross with an expected 3 purple : 1 white ratio. Outcomes Observed (0) Expected (E) O-E (0-E)2 (O-E)²/E Purple White Totals 705 224 929 X²= The first step is to calculate the expected (E) values for purple and…
How are the standard deviation and variance related to each other? How are they different than just measuring the range? Can plot samples of dandelion cover from two different locations have the same mean but different variance? Explain. Can you answer question 3? Thanks.
Example 3.5.7 Fish Vertebrae Consider the distribution of vertebrae given in Table 3.5.1. In Exam- ple 3.5.5 we found that the mean of Y is µy = 21.49. The variance of Y is VAR(Y) = of = (20 – 21.49) x Pr{Y = 20} 21) %3D + (21 – 21.49)? x Pr{Y + (22 – 21.49)? x Pr{Y = 22} + (23 – 21.49) x Pr{Y = 23} = (-1.49) x 0.03 + (-.49) x 0.51 + (0.51) x 0.40 + (1.51)² × 0.06 = 2.2201 x 0.03 + .2401 x 0.51 + .2601 x 0.40 + 2.2801 x 0.06 = 0.066603 + 0.122451 + 0.10404 + 0.136806 = 0.4299. The standard deviation of Y is ay = V0.4299 - 0.6557. %3D
The calculated chi-square value which is 0 is less than the critical value which is 5.991 (under the degree of freedom 2). What is the probability of the computed chi-square value? And is it part of the population in Hardy-Weinberg equilibrium?
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Pretend that you are comparing the actual genotype distribution for a population with the distribution of genotypes predicted by the Hardy-Weinberg theorem. So you hypothesize that the population is in Hardy-Weinberg equilibrium (i.e. that actual population data fit the Hardy-Weinberg expectations). If you carry out chi-square goodness of fit test and calculate a total chi-square value of 0.03 with 1 degree of freedom (see table), what does this mean?