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Here are the calculations based on the provided dataHere are the calculations based on the provided 

1. **Mean**: \( 39.3 \, \text{gm} \)
2. **Median**: \( 38.5 \, \text{gm} \)
3. **Mode**: \( 37 \, \text{gm} \)
4. **Range**: \( 14 \, \text{gm} \) (difference between 47 and 33)
5. **Variance**: \( 19.21 \, \text{gm}^2 \)
6. **Standard Deviation**: \( 4.38 \, \text{gm} \)

Would you like a deeper explanation or more details on any of these? 

Here are some related questions for further exploration:
1. What is the significance of variance in data analysis?
2. How does the mode differ from the mean and median in interpreting data?
3. Can the standard deviation alone determine data spread effectively?
4. Why does the population variance use \( N \) while sample variance uses \( N-1 \)?
5. How would these calculations differ if the data size was much larger?

**Tip**: A small standard deviation indicates that data points are close to the mean, while a large one suggests more spread out data.

At Noodle Factory Limited, the following data were collected every half an hour: X = Weight in gm. Data: [46, 37, 40, 33, 42, 36, 40, 47, 37, 35]. Calculate: (i) Mean, (ii) Median, (iii) Mode, (iv) Range, (v) Variance, (vi) Standard Deviation.

Analyze the weight data collected at Noodle Factory Limited with calculations for Mean, Median, Mode, Range, Variance, and Standard Deviation. Learn how to apply fundamental statistical concepts to a real-world dataset. Suitable for students in Grades 9-10.

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