Answer:
<h3>
"In a linear regression model, the variable that is being predicted or explained is known as <u>
_dependent variable</u>
It is denoted by y and is often referred to as the response variable".</h3>
Step-by-step explanation:
Given that "In a linear regression model, the variable that is being predicted or explained is known as <u>dependent variable</u> It is denoted by y and is often referred to as the response variable".
- Because linear regression models for variables are used to explain or predict the relationship between two variables.
- The variable in the given model that is being predicted is called the dependent variable.
Answer: a) P(x=0) = 0.0907, b) P(x≥10) = 0.7986
Step-by-step explanation: the probability mass function of a possion probability distribution is given as
P(x=r) = (e^-λ)×(λ^r) /r!
Where λ = fixed rate at which the event is occurring and each event is independent of each other = 2.4
a) P(x= at least one) = P(x≥1)
P(x≥1) = 1 - P(x<1)
But P(x<1) = P(x=0) { we can not continue to negative values because our values of x can only take positive values of integer}
Hence, P(x≥1) = 1 - P(x=0)
P(x=0) = e^-2.4 * 2.4^0/(0!)
P(x=0) = 0.0907×1/1
P(x=0) = 0.0907
b) if the average number of hits in 1 minutes is 2.4 then for 5 minutes we have 2.4×5 = 12.
Hence λ = 12.
P(x= at least 10) =P(x≥10) = 1 - P(x≤9)
P(x≤9) will be gotten using a cumulative possion probability distribution table whose area is to the left of the distribution.
From the table P(x≤9) = 0.2014.
P(x≥10) = 1 - 0.20140
P(x≥10) = 0.7986
<h2>
Answer with explanation:</h2>
Let x denotes the number of days and y denotes the total change in gas price ( in dollars).
Given : During the past seven days the price of regular gas is decreased by $0.2 each day.
Rate of decrease =$0.2 per day
Then , Total change in gas price = Rate of decrease x Number of days
i.e.
i.e. 
(1)
To find the total change in gas price in 7 days , we put x= 7 in (1) , we get
Hence, the total change in gas price in 7 days = $1.4
Answer:
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Step-by-step explanation:
Ttttttttttttfffi is the area located in the south of England and its a very well established and flexible working environment with a
