In California, we need more rain to sustain the health of our natural environment, argriculture, and economic. A group of statistics students in Oxnard College recorded the amount of rain during 2016-2017 school year, measuring the intensity by the inches of rain, and the results were:

Inches of Rain	1	2	3	4	5	6
Frequency	4	0	2	3	4	3

The mean (

) rain intensity: Incorrect inches (Please show your answer to 1 decimal place.)

The median rain intensity: Incorrect inches

The mode rain intensity: Incorrect inches (Please separate your answers by ',' in the bimodal situation. Enter DNE if there is no mode or if there are more than two modes.)

We are given the data on rain intensity (in inches) and their respective frequencies:

| Inches of Rain | 1 | 2 | 3 | 4 | 5 | 6 |
|----------------|---|---|---|---|---|---|
| Frequency      | 4 | 0 | 2 | 3 | 4 | 3 |

### 1. Mean Rain Intensity
To calculate the mean, we need to use the formula:

\[
\text{Mean} = \frac{\sum (x \cdot f)}{\sum f}
\]

Where \(x\) is the rain intensity (in inches), and \(f\) is the frequency.

Let's compute the mean.

### 2. Median Rain Intensity
The median is the middle value of the dataset when arranged in ascending order. Since the data is given in a frequency table, we will list out the total number of data points and determine the middle value based on the cumulative frequency.

### 3. Mode Rain Intensity
The mode is the value(s) that occur most frequently. We will identify the value with the highest frequency.

Let's compute these values.### Results:
1. **Mean rain intensity**: 3.8 inches (rounded to 1 decimal place)
2. **Median rain intensity**: 4.0 inches
3. **Mode rain intensity**: 1, 5 inches (bimodal)

Would you like further details or clarifications?

Here are 5 related questions to deepen your understanding:
1. How is the mean affected by extreme values or outliers in a dataset?
2. What is the significance of the median in skewed distributions compared to the mean?
3. Can a dataset have no mode? Under what conditions does that happen?
4. How would the mean change if we increased the frequency for higher rain intensities?
5. How can the shape of the data distribution (e.g., symmetrical, skewed) affect the mean, median, and mode?

**Tip**: In statistics, the mean is sensitive to outliers, whereas the median provides a better measure of central tendency for skewed data.

In California, we need more rain to sustain the health of our natural environment, agriculture, and economy. A group of statistics students in Oxnard College recorded the amount of rain during the 2016-2017 school year, measuring the intensity by the inches of rain, and the results were:
Inches of Rain: 1, 2, 3, 4, 5, 6
Frequency: 4, 0, 2, 3, 4, 3

The mean rain intensity: Incorrect inches (Please show your answer to 1 decimal place.)
The median rain intensity: Incorrect inches
The mode rain intensity: Incorrect inches (Please separate your answers by ',' in the bimodal situation. Enter DNE if there is no mode or if there are more than two modes.)

Learn how to calculate the mean, median, and mode for rain intensity data recorded by students at Oxnard College during the 2016-2017 school year. This problem involves working with a frequency distribution and measures of central tendency, perfect for students in Grades 9-12.

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