how much it weighs: if a ball weighs 1 oz it'll bounce higher
its size: if a ball is small and light it will most likely bounce higher but if its large and heavy it probably wont bounce as high.
( i know its only 2 factors but its right of the top of my head so...… hope i helped... :)
Answer:
True
Step-by-step explanation:
Assume the following
Mean is represented by μ
Standard deviation by σ
Sample mean by x
Sample Size by n
Given that all possible values of a random variable calculated from a sample of size n with a population mean and standard deviation μ and σ, respectively, it's known that the sampling distribution of the sample mean x is its probability distribution.
Having said that, assume that a simple random sample of size n is drawn from a large population with mean μ and standard deviation σ, as stated above.
The sampling distribution of x will be distributed normally as long as the random variable is normally distributed.
<u>Question Completion</u>
- Box A, The rectangular prism is of dimension 3 inch by 4 inch by 10 inch
- Box B, the Triangular prism has a base triangle of base 8 inch and height 3 inch. The length of the triangular prism is 6 Inch
See attached diagram
Answer:
Box B
Step-by-step explanation:
To determine the box which is made with less cardboard, we calculate the Total Surface Area of each box.
<u>Rectangular Prism(Box A)</u>
Total Surface Area=2(LW+LH+WH)
=2(10x4+10x3+3x4)
=
2(40+30+12)
=2(82)
Total Surface Area of Box A = 164 square inches
<u>Triangular Prism (Box B
)</u>
Total Surface Area=2(Area of Triangle)+Area of Base rectangle+2(Area of side rectangles)
=2(0.5X3X8)+(8X6)+2(5X6)
=24+48+60
=132
Total Surface Area of Box B = 132 square inches
Since the total surface area of Box b is lesser,Box B is made with less cardboard .
Answer:
<h3>The purpose of a single linear regression is <u>
To predict a dependent variable from data from multiple independent variables</u></h3>
Step-by-step explanation:
The purpose of a simple linear regression is same as a correlation in that the purpose is to measure a linear relationship between two variables to the end.
In that particular case , its purpose is to "predict" the data from a dependent variable to the data from atleast one independent variable.
<h3>The purpose of a single linear regression is <u>
To predict a dependent variable from data from multiple independent variables</u></h3>
11 feet = 132 inches
The boards are x, x and (x-3) inches long.
x + x + x -3 = 132
3x = 135
x = 45
The boards are 45 inches, 45 inches and 42 inches long.