Final answer:
The question involves statistical hypothesis testing to compare the proportion of technology users across different groups using chi-square tests. These comparisons provide insight into the digital divide affecting how different demographics access and utilize technology, like smartphones and tablet computers.
Step-by-step explanation:
The question relates to statistics, which involves analyzing data to test hypotheses. More specifically, the scenarios involve hypothesis testing to determine whether there are significant differences between groups in their uses of technology such as smartphones, desktop computers, and tablet computers. The analysis will typically require conducting a chi-square test for independence, given that the data is categorical. In both presented cases, proportions of users in different categories, stratified by gender, age, and device type, are compared.
For example, when testing whether more men use smartphones than women at the 5 percent level of significance, we would compare the observed frequencies (379 out of 973 men and 404 out of 1,304 women) to the expected frequencies under the assumption that there is no difference in smartphone use between men and women. This involves calculating the chi-square statistic and comparing it to a critical value from the chi-square distribution. Similarly, when comparing the proportions of tablet users by age groups at the 1 percent level of significance or the use of e-readers by age, we follow the same methodology.
These questions help us understand the digital divide, which is exacerbated by factors such as ethnicity, as suggested by research that indicates significant differences in technology ownership and usage among different racial and ethnic groups. This has implications for access to important online activities, which may be impaired for those who are reliant on smartphones alone for internet access.