Old School versus New School Sports Fans OLDSKOOL\' GENDER Cross-Tabulation Thre

Question

Old School versus New School Sports Fans OLDSKOOL' GENDER Cross-Tabulation Three academic researchers investigated the idea that, in American sports, there are two segments with opposing views about the goal of competition (i.e, winning versus self actualization) and the acceptable/desirable way of achieving this goal. Persons who believe in OLDSKOOL gh Total 26 100.0% 9.6% 9.5% 115 100.0% Women Men Count winning at any cost" are proponents of sports success as a product and can be labeled new school (NS) individuals. The new school is founded on notions of the player before the team, loyalty to the highest bidder, and high-tech production and consumption of professional sports On the other hand, persons who value the process of sports and believe that "how you play the game matters" can be labeled old school (OS) individuals. The old school emerges from old fashioned American notions of the team before the player, sportsmanship, and loyalty above all else, and competition simply for "love of the game." 34.6% 10.6% 3.396 65-496 6 within OLDSKOOL 96 within GENDER 9.2% Count .9% 37.8% 25-996 39.1% 52.9% 16.796 31 24.096 36.5% OLDSKOOL 96 within GENDER 96 of Tot Count New School Old School was measured by asking agreement with ten attitude statements. The scores on these statements were combined. Higher scores represent an orientation toward old school values. For purposes of this case study, individuals who did not answer every question were eliminated from the analysis. Based on their summated scores across the 10 items, respondents were grouped into low score, middle score, and high score groups. The following table shows the SPSS computer output of a cross-tabulation to relate the gender of the respondent (GENDER) with the New School/Old School grouping (OLDSKOOL) 42696 129 100.0% 47.5% 47.8% OLDSKOOL 96 within GENDER % of Total 36.3% To Count 270 1. Interpret the computer output. What do the results presented above indicate? 2. Is the analytical approach used here appropriate? 3. Describe an alternative approach to the analysis of the original data. Which of these two 6 within OLDSKOOL 96 within GEND 31.5% 100.0% 100,0% analyses would you suggest using? Chi-Square Tests Asymp. 31g. (2-sided) Pearson Chi-Square6.557a Likelihood Ratio N of Valid Cases a o cells (.0%) have expected count less than 5. The minimum expected count is 8.19.

Explanation / Answer

(1)

Chi-square test for independence was used to test the association between the two variables GENDER and OLDSCHOOL. The null hypothesis is that the two variables are independent of each other. The alternate hypothesis is that they are associated.

Two test statistics were used -

For both the statistics, the p-value (the significance column) shows values less than 0.05 i.e. at 95% confidence level, we reject the null hypothesis and affirm that the two variables have significant association.

(2)

The following assumptions were checked for the Chi-square test of independence

This makes the Chi-square test good for checking the association between the two variables.

(3)

Three alternatives to Chi-square test are

Fisher's exact test or the Freeman-Halton test is useful when the frequency counts in some of the cells fall below 5. Which is not the case here. For ANOVA, additional constraints are normality and homoskedasticity. So, we will give Chi-square test more preference.

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