Answer:
Choice D
Step-by-step explanation:
The function will be continuous everywhere except where the function in the denominator is 0. We, therefore determine the value(s) of x for which the function will be 0;
Therefore, the points x= 2 and x =4 are points of discontinuity
For the simple random sample, drawn from a normally distributed population, value of 27, because it’s greater than 26. 7 and less than 29. 3.
<h3>What is normally distributed data?</h3>Normally distributed data is the distribution of probability which is symmetric about the mean.
The mean of the data is the average value of the given data. The standard deviation of the data is the half of the difference of the highest value and mean of the data set.
Total number of sample is 60. The mean found to be 28, with a standard deviation of 5. The z-score is 1. 96.
The margin of error can be found out using the following formula as,'
Put the values as,
As, the mean of the sample is 28. Thus, the upper and lower limits are,
Hence, For the simple random sample, drawn from a normally distributed population, value of 27, because it’s greater than 26. 7 and less than 29. 3.
Learn more about the normally distributed data here;
Answer:
a) 3
b) 9
c) 81
d) x
Step-by-step explanation:
We know the properties of log function as:
1) log(AB) = log(A) + log(B)
2)
3) log(aᵇ) = b × log(a)
also,
4)
Given:
a. y =
Now,
taking log both sides, we get
log(y) =
using 3, we get
log(y) = log₃(3) × log(3)
using 4, we get
log(y) = × log(3)
or
log(y) = 1 × log(3)
taking anti-log both sides
y = 3
b. y =
Now,
taking log both sides, we get
log(y) =
using 3, we get
log(y) = log₃(9) × log(3)
using 4, we get
log(y) = × log(3)
or
log(y) = log(9)
taking anti-log both sides
y = 9
c. y =
Now,
taking log both sides, we get
log(y) =
using 3, we get
log(y) = log₃(81) × log(3)
using 4, we get
log(y) = × log(3)
or
log(y) = log(81)
taking anti-log both sides
y = 81
d. y =
Now,
taking log both sides, we get
log(y) =
using 3, we get
log(y) = log₃(x) × log(3)
using 4, we get
log(y) = × log(3)
or
log(y) = log(x)
taking anti-log both sides
y = x