Answer and Step-by-step explanation: Scaterplot is a type of graphic which shows the relationship between to variables. In this question, you want to determine if there is a linear relationship between overhead widths of seals and the weights. So, the hypothesis are:
H₀: no linear correlation;
H₁: there is linear correlation;
In this hypothesis test, to reject H₀, the correlation coefficient r of the data set has to be bigger than the critical value from the table.
With α = 0.05 and n = 6, the critical value is 0.811.
The linear correlation is calculated as:
r = n∑xy - ∑x.∑y / √[n∑x² - (∑x)²] [n∑y² - (∑y)²]
r = 
r = 0.9485
Since r is bigger than the critical value, H₀ is rejected, which means there is enough evidence to conclude that there is linear correlation between overhead widths and the weights.
In the attachments is the scaterplot of the measurements, also showing the relationship.
So you have 5.36
that is 5 wholes and 0.36
0.36 can be written on a fraction of 36/100
simplify it to 9/25
Now you have the mixed number
5 9/25 or to write it into an improper fraction... multiply 25 * 5 then add 9, that is 134/25.
Hope this helps
The answer is -5, -5 added by 5 cancels each other out. Then when you add 4x + 8x, you get 12x. So when you do 12x= -60, you get -5.
The population growth will be modeled using exponential growth:
f(x)=a(b)^t
where:
a=initial value
b=growth rate
thus plugging in the values we get:
f(x)=1.3(1.04)^t
thus the population after 10 years will be:
f(x)=1.3(1.04)^10
f(x)=1.9243
thus the population in 10 years will be:
1.9243 million