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Data Stats and Storybook
Transcript of Data Stats and Storybook
-Dependent variable: The height BUT with height... there are many factors that can influence or control human height Extraneous variables: We had hoped to find- a strong/moderate positive correlation We Used:
- primary and secondary sources of research
- Stratified sample
- Cluster sample
- Voluntary-Response sampling - We have conducted the surveys in 6 various schools around: - We chose to include 4 age groups in our sample (age 12 to age 19)
- In the end, out of the _____ surveys handed out, only ____ were useful 1. The Peel District School Board
2. The Toronto District School Board -Ages 12 to 13 have the average height of [4’9-5’2)
-> Above the 55th percentile
-Ages 14 to 19 have the average height of [5’5-5’9) -LOOK: At the # of activities that each age group participates in
-> FOUND: The younger respondents tend to be more active than the older ones (in both Brampton and Toronto) ->BUT: we have notice that the majority of the tallest tend to participate in no more than three physical activities (The average # being 1.5 activities) - The average # of physical activities is 1.58 (around 1 to 2 activities)
-> MEANS: The majority of our respondents (especially the ones ages 12 to 15) tends to participate in at least 1 physical activity -FOUND: weak positive linear correlation (its correlation coefficient is 0.21325) -LOOK: The relationship between weight-lifting and height -LOOK: The relationship between genetics and height -LOOK: The relationship between height and time spent ->FOUND: The average height tends to spend a mean of 1.03 hour on their physical activities ->FOUND: Genetic factors can determine 60%-80% of the difference in height between people ->FOUND: 107 out of 147 people don’t lift weights; whereas 40 people do participate in weight lifting (80% of them are male) ->BUT: After calculating the correlation coefficient, there seem to be NO relationship Becasue there is a limit on how much physical activity one should do Presented by... Jennifer Maleeha & Weak Positive linear correlation -You always influence your height by practicing a healthy lifestyle that promotes growth whether this includes eating right or getting the right amount of exercise What We Would Change... 1. Change the sampling methods
-> BECAUSE: even though we try to min. the bias, there is always unintentional bias: 3. Should have survey an even number of each age set “Non-Response” bias “Response” bias Ages Gender Amount of Time Genetic Inheritance Weight-lifting Amount of Sleep Diets Type of food Eating habits -Meaning that physical activities cannot change one's height significantly, but only a little -“Prolonged exercise” can actually stunt one’s height because ... Our Survey: -47 students age 12-13
-48 students age 14-15
-32 students age 16-17
-20 students age 18-19 -LOOK: At the overall height per age group
-> FOUND: A majority cluster around the [5’5-5’9) set Ages 12-13 Ages 14-19 Ages 12-13 Ages 14-19 2. Change some of the options in our survey questions Discrete Continuous