When analyzing the multiple regression model, the real estate builder should be concerned with Multicollinearity.
<h3 /><h3>What is Multicollinearity?</h3>
This is a phenomenon in regression analysis where some of the independent variables are correlated. This can present an issue because the correlation leads to less reliable results.
The income in this research is influenced by the education and they both influence family size. There is therefore an issue of multicollinearity here because some variables are correlated.
Find out more on Multicollinearity at brainly.com/question/16021902.
It decrease and it percentage is 53
To do part B, use the equation that you wrote for part A. We need to figure out what month number March of 2020 will be; we started in January 2015 at month 1; month 2 was Feb. 2015; month 3 was Mar. 2015; etc. to month 12 at Dec. 2015. Then month 13 will be Jan. 2016; month 13+12=25 will be Jan. 2017; month 25+12=37 will be Jan. 2018; month 37+12=49 will be Jan. 2019; month 49+12=61 will be Jan. 2020; month 62 will be Feb. 2020; and month 63 will be March 2020.
63 is the number you will substitute for x in the equation you've already written for part A.
Answer:
Step-by-step explanation:
15%(p)
Answer:
A, and D
Step-by-step explanation:
A works because when you multiply like bases, you add exponents, so we have...
5^7*5^-4 = 5^(7+(-4)) = 5^(7 -4) = 5^3
B doesn't work because when you divide like bases, you subtract the exponent of the denominator from the exponent of the denominator...
5^12/5^4 = 5^(12 - 4) = 5^8
C doesn't work because there is addition.
5 + 5² = 5 + 25 = 30, and 5³ = 125
D works because 5^0 = 1, so we have
5^0(5^3) = 1(5^3) = 5^3
E doesn't work because there is subtraction...
5^3 - 5^0 = 5^3 - 1 = 124
