Answer:
Area of rectangular bedroom = 3000 square feet
Step-by-step explanation:
It is given that the total distance around the rectangular bedroom is 220 feet
perimeter of rectangle = total distance around the rectangle
hence the perimeter of rectangle = 220 feet
now width of rectangle = 50 feet
Let us assume the length of rectangular room be L
we have formula
now we plug perimeter = 220 and width = 50
so we have
(divide both side by 2)
(subtract 50 from both side )
Area of rectangular bedroom is given by
Area = length × width
Area = 60 × 50
Area = 3000 square feet
Answer:
Step-by-step explanation:
Answer: Choice A) The number that is 5 to the left of -3 on the number line.
Explanation:
Refer to the diagram below. The value -3 is 3 units to the left of 0 on the number line. So you start at 0 and move 3 spaces to the left to arrive at -3.
Once you're at -3 on the number line, you'll move 5 more spaces to the left to arrive at -8
We can think of -3+(-5) as -3-5, both of which simplify to -8
Or we can think of it like saying -3+(-5) = -1*(3+5) = -1*8 = -8. Here I factored out a negative 1, and then added. The final result is negative since we're moving to the left in the negative territory.
Answer:
1,3,5,15,25,75
Step-by-step explanation:
Answer:
Step-by-step explanation:
Hello!
The variable of interest is
X: mark obtained in an aptitude test by a candidate.
This variable has a mean μ= 128.5 and standard deviation σ= 8.2
You have the data of three scores extracted from the pool of aptitude tests taken.
148, 102, 152
The average is calculated as X[bar]= Σx/n= (148+102+152)/3= 134
An outlier is an observation that is significantly distant from the rest of the data set. They usually represent experimental errors (such as a measurement) or atypical observations. Some statistical measurements, such as the sample mean, are severely affected by this type of values and their presence tends to cause misleading results on a statistical analysis.
Using the mean and the standard deviation, an outlier is any value that is three standard deviations away from the mean: μ±3σ
Using the population values you can calculate the limits that classify an observed value as outlier:
μ±3σ
128.5±3*8.2
(103.9; 153.1)
This means that any value below 103.9 and above 153.1 can be considered an outlier.
For this example, there is only one outlier, that this the extracted score 102
I hope this helps!
