QUESTION IMAGE
Question
- x represents the amount of snow (in inches) that fell in nome, alaska last winter
- x represents the total number of die rolls required for an individual to roll a five
directions: use the frequency distribution to construct a probability distribution. then, find the mean and standard deviation of the probability distribution.
9 dogs the number of dogs per household in a small town
| dogs | 0 | 1 | 2 | 3 | 4 | 5 |
|---|
Step1: Calculate total number of households
First, we find the total number of households by summing up all the frequencies.
Total households \( N = 1491 + 425 + 168 + 48 + 29 + 14 \)
\( N = 1491+425 = 1916 \); \( 1916 + 168 = 2084 \); \( 2084+48 = 2132 \); \( 2132 + 29 = 2161 \); \( 2161+14 = 2175 \)
Step2: Construct probability distribution
The probability \( P(x) \) for each number of dogs \( x \) is given by \( P(x)=\frac{\text{Frequency of }x}{N} \)
- For \( x = 0 \): \( P(0)=\frac{1491}{2175}\approx0.6855 \)
- For \( x = 1 \): \( P(1)=\frac{425}{2175}\approx0.1954 \)
- For \( x = 2 \): \( P(2)=\frac{168}{2175}\approx0.0772 \)
- For \( x = 3 \): \( P(3)=\frac{48}{2175}\approx0.0221 \)
- For \( x = 4 \): \( P(4)=\frac{29}{2175}\approx0.0133 \)
- For \( x = 5 \): \( P(5)=\frac{14}{2175}\approx0.0064 \)
Step3: Calculate the mean (\(\mu\))
The formula for the mean of a probability distribution is \( \mu=\sum_{i}x_iP(x_i) \)
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Step4: Calculate the variance (\(\sigma^2\))
The formula for variance is \( \sigma^2=\sum_{i}(x_i - \mu)^2P(x_i) \)
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Calculate each term:
- First term: \( 0.2516\times1491\approx375.1356 \); \( \frac{375.1356}{2175}\approx0.1725 \)
- Second term: \( 0.2484\times425\approx105.57 \); \( \frac{105.57}{2175}\approx0.0485 \)
- Third term: \( 2.2452\times168\approx377.1936 \); \( \frac{377.1936}{2175}\approx0.1734 \)
- Fourth term: \( 6.2420\times48\approx299.616 \); \( \frac{299.616}{2175}\approx0.1377 \)
- Fifth term: \( 12.2390\times29\approx354.931 \); \( \frac{354.931}{2175}\approx0.1632 \)
- Sixth term: \( 20.2366\times14\approx283.3124 \); \( \frac{283.3124}{2175}\approx0.1303 \)
Sum these terms: \( 0.1725 + 0.0485+0.1734 + 0.1377+0.1632 + 0.1303 = 0.8256 \)
Step5: Calculate the standard deviation (\(\sigma\))
Standard deviation is the square root of variance: \( \sigma=\sqrt{\sigma^2}=\sqrt{0.8256}\approx0.9086 \)
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- Probability Distribution:
| Dogs (\(x\)) | 0 | 1 | 2 | 3 | 4 | 5 |
|---|
- Mean: \(\approx0.50\) (or more precisely \(0.5016\))
- Standard Deviation: \(\approx0.91\) (or more precisely \(0.9086\))