Westonci.ca offers fast, accurate answers to your questions. Join our community and get the insights you need now. Join our Q&A platform to get precise answers from experts in diverse fields and enhance your understanding. Discover detailed answers to your questions from a wide network of experts on our comprehensive Q&A platform.
Sagot :
To solve this problem, we need to identify the correct formulas for calculating the variance and standard deviation based on the given sample data.
### Step 1: Define the Data
We are given the daily heights of bamboo stalks:
[tex]\[ 20, 19, 17, 16, 18, 15, 20, 21 \][/tex]
### Step 2: Calculate the Mean ([tex]\(\bar{x}\)[/tex])
The mean ([tex]\(\bar{x}\)[/tex]) is calculated as:
[tex]\[ \bar{x} = \frac{\sum_{i=1}^n x_i}{n} \][/tex]
where [tex]\( x_i \)[/tex] are the individual heights and [tex]\( n \)[/tex] is the number of observations.
For the given data:
[tex]\[ \bar{x} = \frac{20 + 19 + 17 + 16 + 18 + 15 + 20 + 21}{8} = \frac{146}{8} = 18.25 \][/tex]
### Step 3: Calculate the Sum of Squared Deviations
We calculate the squared deviation of each observation from the mean:
[tex]\[ (x - \bar{x})^2 \][/tex]
For each height:
[tex]\[ (20 - 18.25)^2 = 3.0625 \][/tex]
[tex]\[ (19 - 18.25)^2 = 0.5625 \][/tex]
[tex]\[ (17 - 18.25)^2 = 1.5625 \][/tex]
[tex]\[ (16 - 18.25)^2 = 5.0625 \][/tex]
[tex]\[ (18 - 18.25)^2 = 0.0625 \][/tex]
[tex]\[ (15 - 18.25)^2 = 10.5625 \][/tex]
[tex]\[ (20 - 18.25)^2 = 3.0625 \][/tex]
[tex]\[ (21 - 18.25)^2 = 7.5625 \][/tex]
Summing these squared deviations:
[tex]\[ 3.0625 + 0.5625 + 1.5625 + 5.0625 + 0.0625 + 10.5625 + 3.0625 + 7.5625 = 31.5 \][/tex]
### Step 4: Calculate the Variance
Using formula A:
[tex]\[ s^2 = \frac{(x_1 - \bar{x})^2 + (x_2 - \bar{x})^2 + \ldots + (x_n - \bar{x})^2}{n - 1} \][/tex]
For the data:
[tex]\[ s^2 = \frac{31.5}{8 - 1} = \frac{31.5}{7} = 4.5 \][/tex]
### Step 5: Calculate the Standard Deviation
Using formula B:
[tex]\[ s = \sqrt{\frac{(x_1 - \bar{x})^2 + (x_2 - \bar{x})^2 + \ldots + (x_n - \bar{x})^2}{n - 1}} \][/tex]
For the data:
[tex]\[ s = \sqrt{4.5} \approx 2.1213 \][/tex]
### Conclusion
The variance of the sample is given by formula A:
[tex]\[ s^2 = \frac{(x_1 - \bar{x})^2 + (x_2 - \bar{x})^2 + \ldots + (x_n - \bar{x})^2}{n - 1} \][/tex]
The standard deviation of the sample is given by formula B:
[tex]\[ s = \sqrt{\frac{(x_1 - \bar{x})^2 + (x_2 - \bar{x})^2 + \ldots + (x_n - \bar{x})^2}{n - 1}} \][/tex]
So, the formulas we should use are:
- For variance: Formula A [tex]\( \boxed{A} \)[/tex]
- For standard deviation: Formula B [tex]\( \boxed{B} \)[/tex]
### Step 1: Define the Data
We are given the daily heights of bamboo stalks:
[tex]\[ 20, 19, 17, 16, 18, 15, 20, 21 \][/tex]
### Step 2: Calculate the Mean ([tex]\(\bar{x}\)[/tex])
The mean ([tex]\(\bar{x}\)[/tex]) is calculated as:
[tex]\[ \bar{x} = \frac{\sum_{i=1}^n x_i}{n} \][/tex]
where [tex]\( x_i \)[/tex] are the individual heights and [tex]\( n \)[/tex] is the number of observations.
For the given data:
[tex]\[ \bar{x} = \frac{20 + 19 + 17 + 16 + 18 + 15 + 20 + 21}{8} = \frac{146}{8} = 18.25 \][/tex]
### Step 3: Calculate the Sum of Squared Deviations
We calculate the squared deviation of each observation from the mean:
[tex]\[ (x - \bar{x})^2 \][/tex]
For each height:
[tex]\[ (20 - 18.25)^2 = 3.0625 \][/tex]
[tex]\[ (19 - 18.25)^2 = 0.5625 \][/tex]
[tex]\[ (17 - 18.25)^2 = 1.5625 \][/tex]
[tex]\[ (16 - 18.25)^2 = 5.0625 \][/tex]
[tex]\[ (18 - 18.25)^2 = 0.0625 \][/tex]
[tex]\[ (15 - 18.25)^2 = 10.5625 \][/tex]
[tex]\[ (20 - 18.25)^2 = 3.0625 \][/tex]
[tex]\[ (21 - 18.25)^2 = 7.5625 \][/tex]
Summing these squared deviations:
[tex]\[ 3.0625 + 0.5625 + 1.5625 + 5.0625 + 0.0625 + 10.5625 + 3.0625 + 7.5625 = 31.5 \][/tex]
### Step 4: Calculate the Variance
Using formula A:
[tex]\[ s^2 = \frac{(x_1 - \bar{x})^2 + (x_2 - \bar{x})^2 + \ldots + (x_n - \bar{x})^2}{n - 1} \][/tex]
For the data:
[tex]\[ s^2 = \frac{31.5}{8 - 1} = \frac{31.5}{7} = 4.5 \][/tex]
### Step 5: Calculate the Standard Deviation
Using formula B:
[tex]\[ s = \sqrt{\frac{(x_1 - \bar{x})^2 + (x_2 - \bar{x})^2 + \ldots + (x_n - \bar{x})^2}{n - 1}} \][/tex]
For the data:
[tex]\[ s = \sqrt{4.5} \approx 2.1213 \][/tex]
### Conclusion
The variance of the sample is given by formula A:
[tex]\[ s^2 = \frac{(x_1 - \bar{x})^2 + (x_2 - \bar{x})^2 + \ldots + (x_n - \bar{x})^2}{n - 1} \][/tex]
The standard deviation of the sample is given by formula B:
[tex]\[ s = \sqrt{\frac{(x_1 - \bar{x})^2 + (x_2 - \bar{x})^2 + \ldots + (x_n - \bar{x})^2}{n - 1}} \][/tex]
So, the formulas we should use are:
- For variance: Formula A [tex]\( \boxed{A} \)[/tex]
- For standard deviation: Formula B [tex]\( \boxed{B} \)[/tex]
We hope you found what you were looking for. Feel free to revisit us for more answers and updated information. Your visit means a lot to us. Don't hesitate to return for more reliable answers to any questions you may have. Get the answers you need at Westonci.ca. Stay informed by returning for our latest expert advice.