Answer:
2.5 × 10^-5
<em>please correct me if im wrong</em><em>.</em>
Equation of the line in point slope form is y + 7 = -5(x - 2)
Step-by-step explanation:
- Step 1: Given slope of the line is -5 and passes through the point (x1, y1) = (2,-7). Equation in point slope form is y - y1 = m(x - x1)
⇒ y - (-7) = -5(x - 2)
⇒ y + 7 = -5(x - 2)
Minus 12x both sides
0=5x^2-12x+9
use quadratic formula
for 0=ax^2+bx+c
x=
given
5x^2-12x+9
a=5
b=-12
c=9
remember: i=√-1
The equation of the least-squared regression line is: In(Element) = 2.305 - 0.101(Time).
<h3>What is a regression line?</h3>
A regression line displays the connection between scattered data points in any set. It shows the relation between the dependent y variable and independent x variables when there is a linear pattern.
According to the given problem,
From the table we can see,
ln(Element) is the dependent variable and Time is the independent variable.
The constant = 2.305,
Time = -0.101
Hence, we can conclude, our least squared regression line will be
In (Element) = 2.305 - 0.101 (Time).
Learn more about regression line here: brainly.com/question/7656407
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Answer:
Standard deviation of a normal data distribution is a measure of data dispersion.
Step-by-step explanation:
Standard deviation is used to measure dispersion which is present around the mean data.
The value of standard deviation will never be negative.
The greater the spread, the greater the standard deviation.
Steps-
1. At first, the mean value should be discovered.
2.Then find out the square of it's distance to mean value.
3.Then total the values
4.Then divide the number of data point.
5.the square root have to be taken.
Formula-
SD=
Advantage-
It is used to measure dispersion when mean is used as measure of central tendency.