Answer:
Descriptive
Step-by-step explanation:
Descriptive statistics uses the data that helps to analyse, describe, and elaborate data accurately. It also provides information regarding the population through graphs or tables. Four types of descriptive statistics are measures of frequency, measures of central tendency, measures of dispersion, and measures of position.
The given example in question is <u>descriptive statistics</u>.
A^2 +b^2 =c^2
c^2 will be your hypotenuse
Hope that helps
The estimate of the total sales is $3,055,510.08.
First I created a scatter plot of the data given for yellow golf balls and calculated the linear regression for it. Screenshots are attached.
The regression equation (equation for the line of best fit) was
y = 16488x + 189312, where x represents the year number and y is the total yellow golf balls.
We are concerned with year 4, so we will substitute 4 for x:
y = 16488(4) + 189312 = 255,264
There will be around 255,264 yellow golf balls sold in year 4.
Since the ratio of yellow to white golf balls is 1:5, we can set up a proportion:
1/5 = 255264/x
Cross multiply:
1*x = 5*255264
x = 1,276,320
We expect the company to sell 1,276,320 white golf balls. This makes a total of:
1,276,320 + 255,264 = 1,531,584 total golf balls expected to be sold in year 4.
Since these are sold in boxes of 12, we divide this by 12:
1,531,584/12 = 127,632 boxes expected to be sold
Each box is 23.94:
127632*23.94 = 3,055,510.08
Answer:

Step-by-step explanation:
The given arithmetic sequence is
14,30,46,62
The first term of this sequence is

The common distance is obtained by subtracting a subsequent term from a previous term;
d=30-14
The common difference is
d=16
The recursive formula is given by:

We now plug in the known value for the common difference to get;
