A researcher should use __________________ to analyze data when he has only a sm
ID: 129465 • Letter: A
Question
A researcher should use __________________ to analyze data when he has only a small sample, and he knows that the sample was drawn from a population that is seriously skewed.
inferential statistics.
nonparametric statistics.
parametric statistics.
descriptive statistics.
Which of these analytic techniques can be used to analyze data across three or more conditions of the IV?
1. t test
2. Analysis of variance
3. Chi-square
2 only
1 and 2 only
2 and 3 only
1, 2, and 3
In a chi-square test, we reject the null hypothesis when the obtained chi-square is
lower than the critical tabled value.
higher than the critical tabled value.
close to the mean of the tabled distribution of chi-square.
far from the mean of the tabled distribution of chi-square.
Assume that you test the null hypothesis that there is no significant difference in the frequency with which students choose among the four alternatives when guessing the answer to a difficult question on a four-choice multiple-choice test. You select 24 students at random and compare their answers. The number of students choosing each answer is shown below:
Answer: A B C D
Number of Students Choosing: 3 9 2 10
Under the null hypothesis, what is the EXPECTED number of students choosing answer B?
4
6
9
24
The purpose of a chi-square goodness-of-fit test is to determine whether
sample frequencies are proportional to population frequencies.
sample frequencies are the same as population frequencies.
sample frequencies between two different samples are similar.
sample frequencies are randomly distributed
inferential statistics.
nonparametric statistics.
parametric statistics.
descriptive statistics.
Which of these analytic techniques can be used to analyze data across three or more conditions of the IV?
1. t test
2. Analysis of variance
3. Chi-square
2 only
1 and 2 only
2 and 3 only
1, 2, and 3
In a chi-square test, we reject the null hypothesis when the obtained chi-square is
lower than the critical tabled value.
higher than the critical tabled value.
close to the mean of the tabled distribution of chi-square.
far from the mean of the tabled distribution of chi-square.
Assume that you test the null hypothesis that there is no significant difference in the frequency with which students choose among the four alternatives when guessing the answer to a difficult question on a four-choice multiple-choice test. You select 24 students at random and compare their answers. The number of students choosing each answer is shown below:
Answer: A B C D
Number of Students Choosing: 3 9 2 10
Under the null hypothesis, what is the EXPECTED number of students choosing answer B?
4
6
9
24
The purpose of a chi-square goodness-of-fit test is to determine whether
sample frequencies are proportional to population frequencies.
sample frequencies are the same as population frequencies.
sample frequencies between two different samples are similar.
sample frequencies are randomly distributed
Explanation / Answer
A sample (any number of people) is collected from the population for the purpose of administering different teaching styles. A sample is considered to be the representation of the population. These individuals who are called sample, are assigned to different treatment groups. A sample which is skewed is not normally distributed. A normally distributed sample uses parametric statistics and for a skewed sample, a researcher must use non-parametric samples wherein the data does not require to fit into normal distribution.
Thus, the correct answer is, B.
Analysis of Variance also known as ANOVA is a statistical method used to find the significant difference between one or more than one variables. ANOVA is of two types; one way ANOVA and two way ANOVA. Analysis of variance is also known as f-test. It is used when one variable is manipulated in more than two ways. For example, an experimenter is trying to understand the different teaching styles on pupils. The teaching style is an independent variable which in this case is manipulated in more than two ways to see it's effects on students. A two way ANOVA is used when there are two independent and two dependent variables and both are manipulated in more than two ways.
Thus, the correct answer is, A.
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