Answer:
x=0.59
Step-by-step explanation:
because if u divide 5.9 by 10 it will give u 0.59
and isolate x
Answer:
the answer would be c=81x^28-n I hope it helps!
Answer:
Likely
First option is correct.
Step-by-step explanation:
The probability for occurring the event = 95% = 0.95
Let us understand different types of events:-
- Certain events: If the probability of occurring an even is 1, then it is a certain event.
- Impossible events: If the probability of occurring an even is 0, then it is a impossible event.
- Likely events: If the probability of occurring an even is close to 1, then it is a likely event.
- Unlikely events: If the probability of occurring an even is close to 0, then it is a unlikely event.
Now, the probability for occurring the event = 95% = 0.95, which is close to 1.
Hence, we can conclude that the event is likely.
First option is correct.
Answer:
B. A teacher compares the pre-test and post-test scores of students
Step-by-step explanation:
the answer is true, because it is a good example to compare the tests between students, we know that a matching pair design is a random model and is used when the experiment allows grouping subjects in pairs based on a variable and each pair will receive randomly a different handling, the answer A is not true because in the example all students are uniformly averaged and the variable is not correlated with subgroups, option c is incorrect because the variable was not randomized and generates classification bias and the option d is incorrect because the teacher compares a small sample as her class with a score of a total sample, but does not intervene on her students when selecting the corresponding group
A. False. Consider the identity matrix, which is diagonalizable (it's already diagonal) but all its eigenvalues are the same (1).
b. True. Suppose
is the matrix of the eigenvectors of
, and
is the diagonal matrix of the eigenvalues of
:
Then
In other words, the columns of
are
, which are identically
, and these are the columns of
.
c. False. A counterexample is the matrix
which is nonsingular, but it has only one eigenvalue.
d. False. Consider the matrix
with eigenvalue
and eigenvector
, where
. But the matrix can't be diagonalized.
