The first indication for Franz that a major conflict is developing include the following: C) Prussian soldiers are drilling along his route to school.
What is a conflict?A conflict can be defined as any form of misunderstanding, disagreement, or struggle that arises between two (2) or more parties such as the members of a team, employees, etc., especially due to any of the following reasons;
Differing or diverging opinions and perspectives.An incompatibility.SuperiorityA difficult challenge.An opposing view.In this context, we can reasonably infer and logically deduce that the first indication for Franz to know that a major conflict is developing would be an information which states that the Prussian soldiers are drilling along the route to Franz's school.
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Correct the 3 grammatical errors (a/an/the) in the text below.
Once a year, the college goes on a expedition trip to do charity work abroad. Last year’s trip was to help set up the community garden in South America. This year’s trip will be to Kenya. The trips are expensive, but students can save an lot of money by working together and doing fundraising events
Answer:
Once a year, a college goes on an expedition trip to do charity work abroad. Last year’s trip was to help set up a community garden in South America. This year’s trip will be to Kenya. The trips are expensive, but students can save a lot of money by working together and doing fundraising events.
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Given the simple linear regression model y=b0+b1xi+µ the drive the error variance
The error variance can be Illustrated as σ^2 = E(μ^2) = Var(μ) = (1/n) * ∑(y - (b0 + b1x))^2
How to illustrate the error variance?The simple linear regression model is of the form:
y = b₀ + b₁x + μ
y = the dependent variable
x = the independent variable
b₀ and b₁ = the parameters of the model, and μ is the error term.
The error term represents the difference between the observed value of the dependent variable and the value predicted by the model. In other words, it is the deviation of the observed y from the expected value of y, given the value of x.
The error variance, denoted by σ^2, is a measure of the spread of the error term. It is calculated as the average squared deviation of the error term from its mean value, which is zero:
σ^2 = E(μ^2) = Var(μ) = (1/n) * ∑(y - (b₀ + b₁x))^2
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Complete question
Given the simple linear regression model y=b0+b1xi+µ, derive the error variance.