The number of defective bulbs a company produces varies with each batch. Based on the table, which histogram exhibits the skew o
2 answers:
You might be interested in
Because the random variable x follows a continuous uniform distribution from x=1 to x=5, therefore
p(x) = 1/4, x=[1, 5]
The value of p(x) ensures that the total area under the curve = 1.
The conditional probability p(x > 2.5 | x ≤ 4) is the shaded portion of the curve. Its value is
p(x > 2.5 | x ≤4) = (1/4)*(4 - 2.5) = 0.375
Answer: 0.375
p(x) = 1/4, x=[1, 5]
The value of p(x) ensures that the total area under the curve = 1.
The conditional probability p(x > 2.5 | x ≤ 4) is the shaded portion of the curve. Its value is
p(x > 2.5 | x ≤4) = (1/4)*(4 - 2.5) = 0.375
Answer: 0.375
Answer:
a) R1ºR1 = R1
b) R1ºR2 = R1
c) R1ºR3 =
d) R1ºR4 =
e) R1ºR5 = R1
f) R1ºR6 =
g) R2ºR3 =
h) R3ºR3 = R3
Step-by-step explanation:
R1ºR1
(<em>a,c</em>) is in R1ºR1 if there exists <em>b</em> such that (<em>a,b</em>) is in R1 and (<em>b,c</em>) is in R1. This means that a > b, and b > c. That can only happen if a > c. Therefore R1ºR1 = R1
R1ºR2
This case is similar to the previous one. (<em>a,c</em>) is in R1ºR2 if there exists <em>b</em> such that (<em>a,b</em>) is in R2 and (<em>b,c</em>) is in R1. This means that a ≥ b, and b > c. That can only happen if a > c. Hence R1ºR2 = R1
R1ºR3
(a,c) is in R1ºR3 if there exists b such that a < b and b > c. Independently of which values we use for a and c, there always exist a value of b big enough so that b is bigger than both a and c, fulfilling the conditions. We conclude that any pair of real numbers are related.
R1ºR4
This is similar to the previous one. Independently of the values (a,c) we choose, there is always going to be a value b big enough such that a ≤ b and b > c. As a result any pair of real numbers are related.
R1ºR5
If a and c are related, then there exists b such that (a,b) is in R5 and (b,c) is in R1. Because of how R5 is defined, b must be equal to a. Therefore, (a,c) is in R1. This proves that R1ºR5 = R1
R1ºR6
The relation R6 is less restrictive than the relation R3, if we find 2 numbers, one smaller than the other, in particular we find 2 different numbers. If we had 2 numbers a and c, we can find a number b big enough such that a<b and b >c. In particular, b is different from a, so (a,b) is in R6 and (b,c) is in R1, which implies that (a,c) is in R1ºR6. Since we took 2 arbitrary numbers, then any pair of real numbers are related.
R2ºR3
This is similar to the case R1ºR3, only with the difference that we can take b to be equal to a as long as it is bigger than c. We conclude that any pair of real numbers are related.
R3ºR3
If a and c are real numbers such that there exist b fulfilling the relations a < b and b < c, then necessarily a < c. If a < c, then we can use any number in between as our b. Therefore R3ºR3 = R3
I hope you find this answer useful!
Answer:
A and C
Step-by-step explanation:
A paired t-test is used to compare two population means where you have two samples in which observations in one sample can be paired with observations in the other sample. For example if we have Before-and-after observations we can use it.
And in order to conduct it we need to have some assumptions:
1) The dependent variable must be continuous (interval/ratio).
2) The observations are independent of one another.
3) The dependent variable should be approximately normally distributed.
4) The dependent variable should not contain any outliers.
Let's analyze one by one the options on this case:
A. The methods used to evaluate the mean of the differences between two dependent variables apply if one has 86 IQ scores of taxpayers from Texas and 86 IQ scores of taxpayers from Ohio
We can assume that is true since the two variables are dependent and we are assuming that all the other conditions are satisfied to use the t paired test.
B. The requirement of a simple random sample is satisfied if we have matched pairs of voluntary response data.
That's not neccesary true since is not a requirement in order to use the t pairedtest.
C. If one has more than 23 matched pairs of sample data, one can consider the sample to be large and there is no need to check for normality.
We can assume that is true since we need to ensure normality in order to apply the test and if the sample size is large enough large we can apply the test.
D. If one has twenty matched pairs of sample data, there is a loose requirement that the twenty differences appear to be from a normally distributed population.
False the requirement of normality is important to apply the test not a loose requirement.
E. If one wants to use a confidence interval to test the claim that mu Subscript d Baseline greater than 0 with a 0.01 significance level, the confidence interval should have a confidence level of 98%.
That's not correct the significance level is and that not correspond to the significance level given on this case.