Answer:
1) 675,000.
2) 356,000
Step-by-step explanation:
There are some rules to round off to the nearest thousand.
1. While rounding off to the nearest thousand, if the digit in the hundreds place is between 0 – 4 i.e., < 5, then the hundreds place is replaced by ‘0’.
2. If the digit in the hundreds place is = to or > 5, then the hundreds place is replaced by ‘0’ and the thousands place is increased by 1.
We have given two numerals:
1)<u> 674,620</u>
According to the second rule defined the digit at the hundreds place is greater than 5 than the thousands place will be increased by 1.
The answer is 675,000.
2) <u>355,500</u>
According to the second rule defined the digit at the hundreds place is greater than 5 than the thousands place will be increased by 1.
The answer is 356,000....
Answer: 547
Step-by-step explanation: The margin of error formulae is given below as
Margin of error = critical value ×(σ/√n)
Where σ = standard deviation and n is the sample size.
From our question, margin of error = 0.08
Variance is 1.691,
hence σ = √variance = √1.691
= 1.3.
We will be using a z test for our critical value this is because a soft drink manufacturer will always produce drinks more than 30 in numbers.
The critical value for a 85% confidence interval is 1.44.
Hence critical value is 1.44.
By substituting the parameters, we have that
0.08 = 1.44 × 1.3/ √n
0.08 = 1.873/ √n
By cross multiplying
0.08 × √n = 1.873
√n = 1.873/ 0.08
√n = 23.41
n = (23.41)²
n = 547.
Answer:
b) y = 289.815 when 
Step-by-step explanation:
We are given the following information in the question:

where y is the dependent variable,
are the independent variable.
The multiple regression equation is of the form:

where,
: is the intercept of the equation and is the value of dependent variable when all the independent variable are zero.
: It is the slope coefficient of the independent variable
.
: It is the slope coefficient of the independent variable
.
- The regression coefficient in multiple regression is the slope of the linear relationship between the dependent and the part of a predictor variable that is independent of all other predictor variables.
Comparing the equations, we get:

- This means holding
constant, a change of one in
is associated with a change of 0.5906 in the dependent variable.
- This means holding
constant, a change of 1 in
is associated with a change of 0.4980 in the dependent variable.
b) We have to estimate the value of y
