18 b. What is the null hypothesis? c. What is the value of t obtained. d. What is the value of t-critical α = 0.05 1 tail. d. What might the candidate conclude using α = 0.05 1 tail? e. What type error might the candidate have made? f. Estimate the size of the real effect using omega squared and cohen’s d. Is the effect a large one? ώ2 = tobt2 -1 tobt2 +N-1 ώ2 = Cohen’s d Estimated d = Xbar1-Xbar2 Spooled Spooled=the square root of the pooled variance sp2= SS1+SS2 = n1+n2-2
Contingency Table
A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.
Binomial Distribution
Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.
2. A nurse was hired by a governmental ecology agency to investigate the impact of a lead smelter on the level of lead in the blood of children living near the smelter. Ten children were chosen at random from those living near the smelter. A comparison group of seven children was randomly selected from those living in an area relatively free from possible lead pollution. Blood samples were taken from the children and lead levels determined. The following are the results (scores are in micrograms of lead per 100 milliliters of blood.
Lead Levels
Children living near smelter Children living in unpolluted area
18 9
16 13
21 8
14 15
17 17
19 12
22 11
24
15
18
b. What is the null hypothesis?
c. What is the value of t obtained.
d. What is the value of t-critical α = 0.05 1 tail.
d. What might the candidate conclude using α = 0.05 1 tail?
e. What type error might the candidate have made?
f. Estimate the size of the real effect using omega squared and cohen’s d. Is the effect a large one?
ώ2 = tobt2 -1
tobt2 +N-1
ώ2 =
Cohen’s d
Estimated d = Xbar1-Xbar2
Spooled
Spooled=the square root of the pooled variance
sp2= SS1+SS2 =
n1+n2-2
Estimated d =
g. Do you satisfy the assumption of homogeneity of variance?How do you know?
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