{"id":2549,"date":"2021-11-22T22:00:58","date_gmt":"2021-11-23T03:00:58","guid":{"rendered":"https:\/\/openbooks.macewan.ca\/rcommander\/?post_type=chapter&p=2549"},"modified":"2025-09-11T15:18:31","modified_gmt":"2025-09-11T19:18:31","slug":"1-7-review-questions","status":"publish","type":"chapter","link":"https:\/\/openbooks.macewan.ca\/introstats\/chapter\/1-7-review-questions\/","title":{"raw":"1.7 Review Questions","rendered":"1.7 Review Questions"},"content":{"raw":"
    \r\n \t
  1. In order to study the effect of aspirin on preventing heart disease and stroke for women over 50 years old, 30,000 initially healthy women 50 years of age or older in Canada were randomly selected. These 30,000 women were randomly assigned to either receive 100 mg of aspirin or placebo (vitamin) on alternative days and were monitored for 10 years. The results showed that the percentage of heart disease and stroke is significantly lower in the aspirin group than in the placebo group. Therefore, we claim that aspirin is effective in preventing heart disease and stroke for all women over 50 years old in Canada.\r\n
      \r\n \t
    1. Identify the population and sample in this study.<\/li>\r\n \t
    2. Is this study inferential or descriptive?<\/li>\r\n \t
    3. Is this an observational study or a design experiment?<\/li>\r\n<\/ol>\r\n<\/li>\r\n \t
    4. The following table gives the salaries (in thousand dollars) for physics and computer science (CS) majors obtaining a bachelor\u2019s degree, a master\u2019s degree or a PhD.\r\n\r\n\r\n\r\n
      \r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
      SALARY<\/th>\r\nMAJOR<\/th>\r\nDEGREE<\/strong><\/th>\r\n<\/tr>\r\n<\/thead>\r\n
      51.9<\/td>\r\nPhysics<\/td>\r\nBach<\/td>\r\n<\/tr>\r\n
      58.2<\/td>\r\nPhysics<\/td>\r\nBach<\/td>\r\n<\/tr>\r\n
      49.9<\/td>\r\nPhysics<\/td>\r\nBach<\/td>\r\n<\/tr>\r\n
      50.6<\/td>\r\nPhysics<\/td>\r\nBach<\/td>\r\n<\/tr>\r\n
      51.4<\/td>\r\nPhysics<\/td>\r\nBach<\/td>\r\n<\/tr>\r\n
      43.7<\/td>\r\nPhysics<\/td>\r\nBach<\/td>\r\n<\/tr>\r\n
      52.9<\/td>\r\nPhysics<\/td>\r\nBach<\/td>\r\n<\/tr>\r\n
      59.2<\/td>\r\nPhysics<\/td>\r\nMaster<\/td>\r\n<\/tr>\r\n
      60.5<\/td>\r\nPhysics<\/td>\r\nMaster<\/td>\r\n<\/tr>\r\n
      57.1<\/td>\r\nPhysics<\/td>\r\nMaster<\/td>\r\n<\/tr>\r\n
      59.1<\/td>\r\nPhysics<\/td>\r\nMaster<\/td>\r\n<\/tr>\r\n
      54.9<\/td>\r\nPhysics<\/td>\r\nMaster<\/td>\r\n<\/tr>\r\n
      61.7<\/td>\r\nPhysics<\/td>\r\nMaster<\/td>\r\n<\/tr>\r\n
      62.4<\/td>\r\nPhysics<\/td>\r\nMaster<\/td>\r\n<\/tr>\r\n
      78.2<\/td>\r\nPhysics<\/td>\r\nPhD<\/td>\r\n<\/tr>\r\n
      69.6<\/td>\r\nPhysics<\/td>\r\nPhD<\/td>\r\n<\/tr>\r\n
      70.5<\/td>\r\nPhysics<\/td>\r\nPhD<\/td>\r\n<\/tr>\r\n
      73.2<\/td>\r\nPhysics<\/td>\r\nPhD<\/td>\r\n<\/tr>\r\n
      81.7<\/td>\r\nPhysics<\/td>\r\nPhD<\/td>\r\n<\/tr>\r\n
      74.8<\/td>\r\nPhysics<\/td>\r\nPhD<\/td>\r\n<\/tr>\r\n
      69.8<\/td>\r\nPhysics<\/td>\r\nPhD<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n<\/td>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
      SALARY<\/th>\r\nMAJOR<\/th>\r\nDEGREE<\/th>\r\n<\/tr>\r\n<\/thead>\r\n
      50.8<\/td>\r\nCS<\/td>\r\nBach<\/td>\r\n<\/tr>\r\n
      59.4<\/td>\r\nCS<\/td>\r\nBach<\/td>\r\n<\/tr>\r\n
      55.9<\/td>\r\nCS<\/td>\r\nBach<\/td>\r\n<\/tr>\r\n
      45.1<\/td>\r\nCS<\/td>\r\nBach<\/td>\r\n<\/tr>\r\n
      54.1<\/td>\r\nCS<\/td>\r\nBach<\/td>\r\n<\/tr>\r\n
      50.7<\/td>\r\nCS<\/td>\r\nBach<\/td>\r\n<\/tr>\r\n
      46.8<\/td>\r\nCS<\/td>\r\nBach<\/td>\r\n<\/tr>\r\n
      65.8<\/td>\r\nCS<\/td>\r\nMaster<\/td>\r\n<\/tr>\r\n
      57.5<\/td>\r\nCS<\/td>\r\nMaster<\/td>\r\n<\/tr>\r\n
      66.9<\/td>\r\nCS<\/td>\r\nMaster<\/td>\r\n<\/tr>\r\n
      62.8<\/td>\r\nCS<\/td>\r\nMaster<\/td>\r\n<\/tr>\r\n
      68.5<\/td>\r\nCS<\/td>\r\nMaster<\/td>\r\n<\/tr>\r\n
      69.3<\/td>\r\nCS<\/td>\r\nMaster<\/td>\r\n<\/tr>\r\n
      61.5<\/td>\r\nCS<\/td>\r\nMaster<\/td>\r\n<\/tr>\r\n
      73.3<\/td>\r\nCS<\/td>\r\nPhD<\/td>\r\n<\/tr>\r\n
      65.7<\/td>\r\nCS<\/td>\r\nPhD<\/td>\r\n<\/tr>\r\n
      71.7<\/td>\r\nCS<\/td>\r\nPhD<\/td>\r\n<\/tr>\r\n
      72.5<\/td>\r\nCS<\/td>\r\nPhD<\/td>\r\n<\/tr>\r\n
      73.0<\/td>\r\nCS<\/td>\r\nPhD<\/td>\r\n<\/tr>\r\n
      67.2<\/td>\r\nCS<\/td>\r\nPhD<\/td>\r\n<\/tr>\r\n
      67.5<\/td>\r\nCS<\/td>\r\nPhD<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n
        \r\n \t
      1. Use the most proper graphs to summarize each of the three variables \u201csalary\u201d, \u201dmajor\u201d and \u201ddegree\u201d.<\/li>\r\n \t
      2. Describe the shape of the histogram of salary.<\/li>\r\n<\/ol>\r\n<\/li>\r\n<\/ol>\r\n
        Show\/Hide Answer<\/summary>\r\n
          \r\n \t
        1. \u200c\r\n
            \r\n \t
          1. The population is all women over 50 years old in Canada. The sample is those 30,000 women.<\/li>\r\n \t
          2. This is an inferential study since it generalized the conclusion to the entire population\u2013all women over 50 years old in Canada.<\/li>\r\n \t
          3. This is a designed experiment, since the subjects were randomly assigned<\/strong> to the two different groups.<\/li>\r\n<\/ol>\r\n<\/li>\r\n \t
          4. \u200c\r\n
              \r\n \t
            1. The variable \"salary\" is a quantitative continuous variable, we can use histogram, boxplot or stem-and-leaf diagram to summarize it. Both \"major\" and \"degree\" are qualitative variables, we can use either a pie chart or a bar chart to summarize them.<\/li>\r\n \t
            2. It is bimodal. It is hard to tell whether it is symmetric or skewed. We might be able to tell the shape better if we draw a boxplot as well.<\/a>[caption id=\"attachment_2553\" align=\"aligncenter\" width=\"505\"]\"Histogram Figure 1.10<\/strong> [Image Description (See Appendix D Figure 1.10)<\/a>][\/caption]<\/li>\r\n<\/ol>\r\n<\/li>\r\n<\/ol>\r\n<\/details>","rendered":"
                \n
              1. In order to study the effect of aspirin on preventing heart disease and stroke for women over 50 years old, 30,000 initially healthy women 50 years of age or older in Canada were randomly selected. These 30,000 women were randomly assigned to either receive 100 mg of aspirin or placebo (vitamin) on alternative days and were monitored for 10 years. The results showed that the percentage of heart disease and stroke is significantly lower in the aspirin group than in the placebo group. Therefore, we claim that aspirin is effective in preventing heart disease and stroke for all women over 50 years old in Canada.\n
                  \n
                1. Identify the population and sample in this study.<\/li>\n
                2. Is this study inferential or descriptive?<\/li>\n
                3. Is this an observational study or a design experiment?<\/li>\n<\/ol>\n<\/li>\n
                4. The following table gives the salaries (in thousand dollars) for physics and computer science (CS) majors obtaining a bachelor\u2019s degree, a master\u2019s degree or a PhD.
                  \n\n\n\n
                  \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
                  SALARY<\/th>\nMAJOR<\/th>\nDEGREE<\/strong><\/th>\n<\/tr>\n<\/thead>\n
                  51.9<\/td>\nPhysics<\/td>\nBach<\/td>\n<\/tr>\n
                  58.2<\/td>\nPhysics<\/td>\nBach<\/td>\n<\/tr>\n
                  49.9<\/td>\nPhysics<\/td>\nBach<\/td>\n<\/tr>\n
                  50.6<\/td>\nPhysics<\/td>\nBach<\/td>\n<\/tr>\n
                  51.4<\/td>\nPhysics<\/td>\nBach<\/td>\n<\/tr>\n
                  43.7<\/td>\nPhysics<\/td>\nBach<\/td>\n<\/tr>\n
                  52.9<\/td>\nPhysics<\/td>\nBach<\/td>\n<\/tr>\n
                  59.2<\/td>\nPhysics<\/td>\nMaster<\/td>\n<\/tr>\n
                  60.5<\/td>\nPhysics<\/td>\nMaster<\/td>\n<\/tr>\n
                  57.1<\/td>\nPhysics<\/td>\nMaster<\/td>\n<\/tr>\n
                  59.1<\/td>\nPhysics<\/td>\nMaster<\/td>\n<\/tr>\n
                  54.9<\/td>\nPhysics<\/td>\nMaster<\/td>\n<\/tr>\n
                  61.7<\/td>\nPhysics<\/td>\nMaster<\/td>\n<\/tr>\n
                  62.4<\/td>\nPhysics<\/td>\nMaster<\/td>\n<\/tr>\n
                  78.2<\/td>\nPhysics<\/td>\nPhD<\/td>\n<\/tr>\n
                  69.6<\/td>\nPhysics<\/td>\nPhD<\/td>\n<\/tr>\n
                  70.5<\/td>\nPhysics<\/td>\nPhD<\/td>\n<\/tr>\n
                  73.2<\/td>\nPhysics<\/td>\nPhD<\/td>\n<\/tr>\n
                  81.7<\/td>\nPhysics<\/td>\nPhD<\/td>\n<\/tr>\n
                  74.8<\/td>\nPhysics<\/td>\nPhD<\/td>\n<\/tr>\n
                  69.8<\/td>\nPhysics<\/td>\nPhD<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/td>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
                  SALARY<\/th>\nMAJOR<\/th>\nDEGREE<\/th>\n<\/tr>\n<\/thead>\n
                  50.8<\/td>\nCS<\/td>\nBach<\/td>\n<\/tr>\n
                  59.4<\/td>\nCS<\/td>\nBach<\/td>\n<\/tr>\n
                  55.9<\/td>\nCS<\/td>\nBach<\/td>\n<\/tr>\n
                  45.1<\/td>\nCS<\/td>\nBach<\/td>\n<\/tr>\n
                  54.1<\/td>\nCS<\/td>\nBach<\/td>\n<\/tr>\n
                  50.7<\/td>\nCS<\/td>\nBach<\/td>\n<\/tr>\n
                  46.8<\/td>\nCS<\/td>\nBach<\/td>\n<\/tr>\n
                  65.8<\/td>\nCS<\/td>\nMaster<\/td>\n<\/tr>\n
                  57.5<\/td>\nCS<\/td>\nMaster<\/td>\n<\/tr>\n
                  66.9<\/td>\nCS<\/td>\nMaster<\/td>\n<\/tr>\n
                  62.8<\/td>\nCS<\/td>\nMaster<\/td>\n<\/tr>\n
                  68.5<\/td>\nCS<\/td>\nMaster<\/td>\n<\/tr>\n
                  69.3<\/td>\nCS<\/td>\nMaster<\/td>\n<\/tr>\n
                  61.5<\/td>\nCS<\/td>\nMaster<\/td>\n<\/tr>\n
                  73.3<\/td>\nCS<\/td>\nPhD<\/td>\n<\/tr>\n
                  65.7<\/td>\nCS<\/td>\nPhD<\/td>\n<\/tr>\n
                  71.7<\/td>\nCS<\/td>\nPhD<\/td>\n<\/tr>\n
                  72.5<\/td>\nCS<\/td>\nPhD<\/td>\n<\/tr>\n
                  73.0<\/td>\nCS<\/td>\nPhD<\/td>\n<\/tr>\n
                  67.2<\/td>\nCS<\/td>\nPhD<\/td>\n<\/tr>\n
                  67.5<\/td>\nCS<\/td>\nPhD<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
                    \n
                  1. Use the most proper graphs to summarize each of the three variables \u201csalary\u201d, \u201dmajor\u201d and \u201ddegree\u201d.<\/li>\n
                  2. Describe the shape of the histogram of salary.<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n
                    \nShow\/Hide Answer<\/summary>\n
                      \n
                    1. \u200c\n
                        \n
                      1. The population is all women over 50 years old in Canada. The sample is those 30,000 women.<\/li>\n
                      2. This is an inferential study since it generalized the conclusion to the entire population\u2013all women over 50 years old in Canada.<\/li>\n
                      3. This is a designed experiment, since the subjects were randomly assigned<\/strong> to the two different groups.<\/li>\n<\/ol>\n<\/li>\n
                      4. \u200c\n
                          \n
                        1. The variable “salary” is a quantitative continuous variable, we can use histogram, boxplot or stem-and-leaf diagram to summarize it. Both “major” and “degree” are qualitative variables, we can use either a pie chart or a bar chart to summarize them.<\/li>\n
                        2. It is bimodal. It is hard to tell whether it is symmetric or skewed. We might be able to tell the shape better if we draw a boxplot as well.<\/a>
                          \n
                          \"Histogram
                          Figure 1.10<\/strong> [Image Description (See Appendix D Figure 1.10)<\/a>]<\/figcaption><\/figure>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<\/details>\n","protected":false},"author":19,"menu_order":7,"template":"","meta":{"pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"class_list":["post-2549","chapter","type-chapter","status-publish","hentry"],"part":34,"_links":{"self":[{"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/pressbooks\/v2\/chapters\/2549","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/wp\/v2\/users\/19"}],"version-history":[{"count":20,"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/pressbooks\/v2\/chapters\/2549\/revisions"}],"predecessor-version":[{"id":5480,"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/pressbooks\/v2\/chapters\/2549\/revisions\/5480"}],"part":[{"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/pressbooks\/v2\/parts\/34"}],"metadata":[{"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/pressbooks\/v2\/chapters\/2549\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/wp\/v2\/media?parent=2549"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/pressbooks\/v2\/chapter-type?post=2549"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/wp\/v2\/contributor?post=2549"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/wp\/v2\/license?post=2549"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}