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Sia

知祁's Question
Math
Posted 10 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 10 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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