Answer:
table:
.1, .25, .35, .2, .1
p(x=4) = .1
p(x<2) = .35
p(3≤x≤4)= .55
1.95, 1.12
Step-by-step explanation:
this is kind of hard to read, but i think i've got it
mean:
0*.1+1*.25+2*.35+3*.2+4*.1= 1.95
The second moment:
0²*.1+1²*.25+2²*.35+3²*.2+4²*.1= 5.05
the variance is the second moment minus the first moment squared (first moment is the mean) and then the standard deviation is the square root of the mean
5.05-1.95²= 1.2475 √1.2475= 1.1169 or 1.12
Answer:
the answer would be anything 11 and under (11,10,9,8,7,6,5,4,3,2,1,0)
Step-by-step explanation:
This is because if n+5 is less than or equal to 16 then 11+5=16 so that is equal to and less than would be using any number less than 11
hope this helps ;)
Answer:
B (300, 400)
Step-by-step explanation:
The profit maximization will be when the sum of the products will be greater. The maximum profit will be when x is 300 and y is 400. If we put in the equation :
P = 40x + 55 y
A - When x = 0 , y = 500
P = [40 * 0] + [55 * 500]
P = 27500
B -
When x = 300 , y = 400
P = [40 * 300] + [55 * 400]
P = 34000
C -
When x = 380 , y = 200
P = [40 * 380] + [55 * 200]
P = 26200
D -
When x = 400 , y = 0
P = [40 * 400] + [55 * 400]
P = 16000
Answer:
Statistical
Step-by-step explanation:
This is a statistical question because we can accumulate data and determine the weight of spider monkeys and owl monkeys
B0 AND B1 are the parameters which describes the intercept and slope of the lines.
According to statement
we have to find the parameters which describes the intercept and slopes.
Simple linear regression is a model that estimates the relationship between one independent variable and one dependent variable using a straight line. Both variables should be quantitative.
So, B0 AND B1 are the parameters which describes the intercept and slope of the lines.
Learn more about SLOPES here brainly.com/question/3493733
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