Hello, I need help with part two. Introduction.

Crosstabs Likes watching Movies ' Gender Likes watching Movies Total Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent 103 99.1% 1 0.9% 109 100.0% Likes watching Movies " Gender Crosstabulation Gender Male Female Total Like Count 20 78 98 Expected Count 18.1 79.9 98.0 %within Likes watching 20.4% 79.6% 100.0% Movies 95 within Gender 100.0% 83.6% 90.7% Dislike Count CI 4 4 Expected Count .7 3.3 4.0 %within Likes watching 0.095 100.095 100.095 Movies 96 within Gender 00% 4.5% 3.7% Don't Care Count 0 6 6 Expected Count 11 4.9 6.0 %within Likes watching 0.0% 100.0% 100.0% Movies 96 within Gender 0.096 6.8% 5.0% Count 20 88 108 Expected Count 20.0 83.0 108.0 %within Likes watching 10.5% 01.5% 100.0% Movies 96 within Gender 100.0% 100.0% 100.0% Chi-Square Tests Asymptotic Significance Value df (2-sided) Pearson Chi-Square 2.505 2 286 Likelihood Ratio 4.322 2 .115 Linear-by-Linear 2.249 .134 Association N of Valid Cases 108 a. 4 cells (66.7%) have expected count less than 5. The minimum expected count is .74. Symmetric Measures Approximate Value Significance Nominal by Nominal Phi .152 .286 Cramer's V .152 286 N of Valid Cases 108Part II: APA Results Section After you have completed Part I, report your findings by creating an APA results section. You must follow all APA formatting guidelines. Use the example provided in this assignment and sample write-up posted on course website as a guide to report your results. Remember to use the correct Greek letter chi "x" (Select Insert, Symbol in Word) and superscript the "2". Be sure to address the following when reporting your results for both chi-square analyses in your write-up. What is your research question? What is your hypothesis or prediction and why? . The obtained results of the analysis. What is the chi-square value and the significance level? Is it statistically significant? What is the effect size as determined by Cramer's V or the phi coefficient value? An interpretation of the results. In your output, note if there are cells with expected counts of less than 5-if so, the results may be invalid. For the purpose of this assignment, if you have more than 20% of the cells with expected frequencies of less than 5, continue with the analysis but address this in your results section (see sample write-up). Also, figuring out the source of the percentages in the tables and interpret what they mean is very important. Make sure you report the percentages that will answer your research question and clarify the relationship (or lack thereof). Example chi-square results section: The research question is whether gender is related to interest in computers. Are males more interested in computers than females? It is predicted that males are more interested in computers because... [Please state why you believe a relationship exists. ] The chi-square test of independence showed a significant relationship between gender and computer interest, x2(2, N = 243) = 6.55, p =.033. The Cramer's V correlation coefficient was .22 suggesting a moderate relationship. OR HERE IS AN EXAMPLE FOR A NONSIGNIFICANT FINDING -- The chi-square test of independence showed the relationship between gender and computer interest was not significant, x2(2, N = 349) = .79, p = .882. The Cramer's V correlation coefficient was .05 indicating a weak relationship. [The values inside the parentheses are the degrees of freedom (df = Rows-1 x Columns-1) and total sample size. Results showed that 74.4% of the males indicated they were interested while 48.2% of the female respondents said they were interested. This is consistent with the hypothesis that males are more interested in computers than are females. [If table is larger than 2x2, report:] Follow-up pairwise comparisons are needed to evaluate the differences among the cells. OR HERE IS A NONSIGNIFICANT FINDING DESCRIPTION -- Results indicated that there was no significant relationship between gender and computer interest. Forty-five percent of the males reported they were interested and 39% of the females said they were interested. This is opposite of what was predicted. Perhaps the reason is... However, it should be noted that the results may be invalid because 75% of the cells had expected frequency of less than five.Crosstabs Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent Employed? * Gender 104 95.4% 5 4.6% 109 100.0% Employed? * Gender Crosstabulation Gender Male Female Total Employed? Full-time Count 3 13 16 Expected Count 2.8 13.2 16.0 % within Employed? 18.8% 81.3% 100.0% % within Gender 16.7% 15.1% 15.4% Part-time Count 11 57 68 Expected Count 11.8 56.2 68.0 % within Employed? 16.2% 83.8% 100.0% % within Gender 61.1% 66.3% 65.4% Do not Work Count 4 16 20 Expected Count 3.5 16.5 20.0 % within Employed? 20.0% 80.0% 100.0% % within Gender 22.2% 18.6% 19.2% Total Count 18 86 104 Expected Count 18.0 86.0 104.0 % within Employed? 17.3% 82.7% 100.0% % within Gender 100.0% 100.0% 100.0% Chi-Square Tests Asymptotic Significance Value df (2-sided) Pearson Chi-Square .185 N .911 Likelihood Ratio .182 N 913 Linear-by-Linear 018 892 Association N of Valid Cases 104 a. 2 cells (33.3%) have expected count less than 5. The minimum expected count is 2.77.Symmetric Measures Approximate Value Significance Nominal by Nominal Phi 042 .911 Cramer's V .042 .911 Contingency Coefficient .042 .911 N of Valid Cases 104