In: Statistics and Probability
To what extent do syntax textbooks, which analyze the structure of sentences, illustrate gender bias? A study of this question sampled sentences from 10 texts. One part of the study examined the use of the words "girl," "boy," "man," and "woman." We will call the first two words juvenile and the last two adult. Is the proportion of female references that are juvenile (girl) equal to the proportion of male references that are juvenile (boy)? Here are data from one of the texts:
Gender | n | X(juvenile) |
Female | 62 | 47 |
Male | 133 | 50 |
(a) Find the proportion of juvenile references for females and its standard error. Do the same for the males. (Round your answers to three decimal places.)
p̂F | = _______ |
SEF | = _______ |
p̂M | = _______ |
SEM | = _______ |
(b) Give a 90% confidence interval for the difference. (Do not use
rounded values. Round your final answers to three decimal
places.)
_______, _______ |
(c) Use a test of significance to examine whether the two
proportions are equal. (Use p̂F −
p̂M. Round your value for z to two
decimal places and round your P-value to four decimal
places.)
z | = | _______ |
P-value | = | _______ |
State your conclusion.
There is sufficient evidence to conclude that the two proportions are different.
There is not sufficient evidence to conclude that the two proportions are different.
Solution:-
a) The proportion of juvenile references for females and its standard error are
p̂F | = 0.758 |
SEF | = 0.054 |
p̂M | = 0.376 |
SEM | = 0.042 |
(b) 90% confidence interval for the difference is C.I =
(0.256, 0.509).
0.256, 0.509 |
C.I = (0.758 - 0.376) + 1.645 × 0.0769
C.I = 0.382 + 0.1265
C.I = (0.256, 0.509)
(c)
z | = | 4.97 |
P-value | = | 0.0000 |
State the hypotheses. The first step is to state the null hypothesis and an alternative hypothesis.
Null hypothesis: P1 = P2
Alternative hypothesis: P1 P2
Note that these hypotheses constitute a two-tailed test. The null hypothesis will be rejected if the proportion from population 1 is too big or if it is too small.
Formulate an analysis plan. For this analysis, the significance level is 0.05. The test method is a two-proportion z-test.
Analyze sample data. Using sample data, we calculate the pooled sample proportion (p) and the standard error (SE). Using those measures, we compute the z-score test statistic (z).
p = (p1 * n1 + p2 *
n2) / (n1 + n2) =
p = 0.4974
SE = sqrt{ p * ( 1 - p ) * [ (1/n1) + (1/n2)
] }
SE = 0.0769
z = (p1 - p2) / SE
z = 4.97
where p1 is the sample proportion in sample 1, where p2 is the sample proportion in sample 2, n1 is the size of sample 1, and n2 is the size of sample 2.
Since we have a two-tailed test, the P-value is the probability that the z-score is less than -2.13 or greater than 2.13.
Thus, the P-value = 0.00
Interpret results. Since the P-value (0.00) is less than the significance level (0.05), we have to reject the null hypothesis.
There is sufficient evidence to conclude that the two proportions are different.