The assumptions of a regression model can be evaluated by plotting and analyzing the error terms.
Important assumptions in regression model analysis are
- There should be a linear and additive relationship between dependent (response) variable and independent (predictor) variable(s).
- There should be no correlation between the residual (error) terms. Absence of this phenomenon is known as auto correlation.
- The independent variables should not be correlated. Absence of this phenomenon is known as multi col-linearity.
- The error terms must have constant variance. This phenomenon is known as homoskedasticity. The presence of non-constant variance is referred to heteroskedasticity.
- The error terms must be normally distributed.
Hence we can conclude that the assumptions of a regression model can be evaluated by plotting and analyzing the error terms.
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Add 2 to both sides...x>3
Answer:
D'G' = 52.5 units
Step-by-step explanation:
Since the dilatation is centred at the origin then multiply the original coordinates by the scale factor 3.5
D' = (1 × 3.5, 7 × 3.5 ) = (3.5, 24.5 )
G' = (- 8 × 3.5, - 5 × 3.5 ) = (- 28, - 17.5 )
Calculate D'G' using the distance formula
d = 
with (x₁, y₁ ) = D' (3.5, 24.5) and (x₂, y₂ ) = G' (- 28, - 17.5)
D'G' = 
= 
= 
= 
= 52.5 units
Answer: L, J, K
Step-by-step explanation:
L, J, and K are collinear because they all lie on the same line.
Answer:
5000 students appeared in the examination.
Step-by-step explanation:
We solve this question using Venn probabilities.
I am going to say that:
Event A: Passed in Mathematics
Event B: Passed in English.
5% failed in both subjects
This means that 100 - 5 = 95% pass in at least one, which means that 
80% passed in mathematics 75% passed in english
This means that 
Proportion who passed in both:

Considering the values we have for this problem

3000 of them were passed both subjects how many students appeared in the examination?
3000 is 60% of the total t. So



5000 students appeared in the examination.