<span>Linear regression is a method of finding the linear equation that comes closest to fitting a collection of data points.
</span>The better the choice of line, the closer the predicted values will be to the observed values.
The differences between the data pints (observed values) and the estimated (pedicted) regression line is called the <span>residue.
</span>Residue = Observed Value -<span> Predicted Value</span>
Percent Change = New Value − Old Value|Old Value| × 100%
Example: There were 200 customers yesterday, and 240 today:
240 − 200|200|× 100% = 40200 × 100% = 20%
A 20% increase.
Percent Error = |Approximate Value − Exact Value||Exact Value| × 100%
Example: I thought 70 people would turn up to the concert, but in fact 80 did!
|70 − 80||80| × 100% = 1080 × 100% = 12.5%
I was in error by 12.5%
(Without using the absolute value, the error is −12.5%, meaning I under-estimated the value)
The difference between the two is that one states factual calculations and the other is a theoretical guess
amount after 2 years = 6000(1 + (0.04/12))^24 = 6498.86
Answer:
c.) aₙ = 5 × 4ⁿ⁻¹
Explanation:
Geometric sequence: aₙ = a(r)ⁿ⁻¹
where 'a' resembles first term of a sequence, 'r' is the common difference.
Here sequence: 5, 20, 80, 320,...
First term (a) = 5
Common difference (d) = second term ÷ first term = 20 ÷ 5 = 4
Hence putting into equation: aₙ = 5(4)ⁿ⁻¹
Answer:
ithink its a or c
Step-by-step explanation:
not sure but dang what grade u in??
