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Sia

知祁's Question
Math
Posted 8 months ago
Recent studies have found that Australian children are more obese than in the past. The amount of time children spent watching television has received much of the blame. A survey of 100 ten-year-olds revealed the following with regards to weights and average number of hours a day spent watching television.
\begin{tabular}{|c|c|c|c|c|}
\hline & & \multicolumn{3}{|c|}{ TV Hours } \\
\hline & & 030-3 hours & 363-6 hours & 6+6+ hours \\
\hline \multirow{4}{*}{ Weights } & More than 10kg overweight & 1 & 9 & 20 \\
\cline { 2 - 6 } & Within 10kg of normal weight & 20 & 15 & 15 \\
\cline { 2 - 6 } & More than 10kg underweight & 10 & 5 & 5 \\
\hline
\end{tabular}

You are interested in testing whether the average number of hours spent watching TV and weights are independent at the 1%1 \% level of significance. If the weights and mean number of hours spent watching TV are independent, what is the expected number of children who spend more than 6 hours on average watching TV and are more than 10 kg10 \mathrm{~kg} overweight?

Answer: \square (Please provide your answer to 1 decimal place).
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Answer from Sia
Posted 8 months ago
Solution by Steps
step 1
Calculate the total number of children surveyed
step 2
Determine the marginal totals for each row and column
step 3
Calculate the expected frequency for children more than 10kg overweight and watching more than 6 hours of TV
step 4
Use the formula for expected frequency: Eij=(row total)×(column total)grand totalE_{ij} = \frac{(row~total) \times (column~total)}{grand~total}
step 5
Plug in the values to find the expected frequency for the specified cell
Answer
[Insert final answer here]
Key Concept
Chi-Square Test of Independence
Explanation
The expected frequency is calculated to determine if there is a significant association between two categorical variables in a contingency table.

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