From the several inferential statistics discussed in class, name the ONE statist

Question

From the several inferential statistics discussed in class, name the ONE statistic (or its symbol) that is appropriate for responding to each of the following hypotheses: Thinking from a logical perspective, only, I would use what statistic to test the hypothesis: There is no difference between people from DC and those from JC in the ranks of their scores on about delinquency. Thinking from a practical perspective, I would use what statistic to test the hypothesis: There is no difference between people from DC and those from JC in the ranks of their continuously distributed scores on attitudes about delinquency. Thinking from a logical perspective, only, I would use what statistic to test the hypothesis: There is no difference between the cities of JC and DC in the mean annual income ($ per year). I used what statistics to come to the conclusion that: For every additional pound I gain, my height will decrease by .1 inch, on average. Thinking from a logical perspective, only, I would use what statistic to test the hypothesis: There is no correlation between nationality and type of religion practiced. Thinking from a logical perspective, only, would use what statistic to test the hypothesis: As the number of LPNs in a hospital decrease, the number of RNs in the same hospital will not decrease Thinking from a logical perspective, only, I would use what statistic to test the hypothesis: There is no difference between nursery, kindergarten, and first grade students in whether their favorite color is red or green or black. Write the response requested, or the word 'true' or 'false for items 1 to 6. Let's say you found the probability (p) of type 1 error to be 02 for the observed t-test on your computer output, you should reject your null hypothesis. An observed X^2 of 11.35 [for H_0: I expect no difference between freshmen, sophomores, juniors, and seniors in the number of these students passing or failing Elementary Statistics; alpha = .01] is statistically significant (i.e., the hypothesis tested should be rejected). A r equal to 1.21 shows a very very high correlation. A r of -45 shows moderate substantive significance. Expressing r_xy = .32 as a PRE measure tells us that we can reduce the error in predicting y by 32% if we know X. r_xy = .32 tells me that as X increases. Y increases. For the data below, what is the Pearson (r) correlation between x (males' height in inches) and y(males' youngest offspring's weight in pounds), where the values (see of x are: and values of y are: If X is 10, for the data in problem 7 above, I predict Y to be. Write the value for X^2 in the blank for the tabular data (cell a = 12, cell b = 12, cell c = 20, cell d = 12, cell e = 12, cell f = 6), where the H_0 for this data is: there is no difference between Republicans & Democrats & Independents in voting for the republican or democratic candidate. Sigma [(fo - fe)^2/fe], where fe = [rt (ct)/n.

Explanation / Answer

I)

1) & 2) Chi-square test of independence.

3) t test for equality of two mean.

4) coefficient of regression

5) correlation coefficient

7) chi-square test for association of attributes.

Related Questions

Navigate

• Browse (All)
• Browse F
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.