工 23 25 28

36 46

14-265--12.5

20-26.5-(2.)

36-26.5-9.5 (3.) 26.5-19.5

10 - 26.5 = - 6.5

- 26.5 = - 3.5

感 (6.) Box= 42.25 (- 12.5) ^ 2 = 156.25

(- 6.5) ^ 2 = 42.25 (19.5) ^ 2 =(8.)

(9.5) ^ 2 =(7.)

(- 3.5) ^ 2 = 12.25

(x - lambda) ^ 2

20

25 (4.)

(9.

(10.)

=-1.5

28-26.5 (5.)

sum(x- overline x )^ 2 = 728

It seems like you've shared a set of numbers and equations that might be part of a mathematical or statistical problem. From the text, I can see various values and operations that seem related to summation, squared terms, and differences, which are often used in calculating variance or standard deviation.

Let me try to interpret this step-by-step and point out the key parts:

1. **Differences and Squaring Terms**:
    - You have several squared terms:  
      \((-12.5)^2 = 156.25\), \((-6.5)^2 = 42.25\), \((-3.5)^2 = 12.25\).  
      These terms seem to be differences between values (possibly \(x - \bar{x}\)) that are squared.

2. **(x - λ)^2**:
    - This looks like a generic form of a squared difference. Perhaps you are calculating something like a deviation from a mean or a parameter \(\lambda\).

3. **Sum of Squares**:
    - The final term indicates:  
      \(\sum (x - \bar{x})^2 = 728\).  
      This could suggest you're working on a variance calculation or the sum of squared deviations from a mean.

4. **Numbers Related to the Calculation**:
    - The numbers in the first two lines (23, 25, 28, etc.) might be data points or related to a distribution.
    - Further expressions like \(10 - 26.5 = -6.5\) and similar operations suggest calculating residuals or deviations from a particular value (possibly a mean).

5. **Box Term**:
    - You have a Box-related expression involving squaring:  
      \(Box = 42.25 (-12.5)^2 = 156.25\).  
      This might refer to part of a statistical method, such as a chi-square or a step in a regression calculation.

If you could provide more context (for example, whether you're working on variance, regression, or another statistical problem), I can assist more precisely in solving this!

Would you like me to go through each part in detail and clarify any specific calculation? 

---

### 5 Related Questions:
1. Are the numbers you provided data points, or part of a larger statistical dataset?
2. Is the expression \((x - \lambda)^2\) related to a parameter you are estimating?
3. Are you calculating variance, standard deviation, or another summary statistic?
4. Does the Box term relate to a specific method like Box-Cox transformation or another statistical technique?
5. Are the final residuals in terms of \(x - \bar{x}\) deviations from a mean or target value?

#### Tip:
For variance or standard deviation calculations, squaring the deviations (differences from the mean) is essential to remove negative values, allowing for accurate measure of spread or dispersion in the dataset.

Explore the step-by-step solution for calculating variance using squared deviations from the mean. This problem involves key statistical concepts such as summation of squares, residuals, and variance. Ideal for students in Grades 10-12.

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