"the difference of a number x and 4": x - 4
"is": =
"3": 3
Combine the terms so that it looks like the sentence numerically:
"the difference of a number x and 4 is 3": x - 3 = 4
x - 3 = 4 is your answer.
To solve for x:
Note the equal sign, what you do to one side, you do to the other. Isolate the variable, x. Add 3 to both sides.
x - 3 = 4
x -3 (-3) = 4 (-3)
x = 4 - 3
x = 1
1 is your answer for x.
~
~
To answer this
problem, we use the binomial distribution formula for probability:
P (x) = [n!
/ (n-x)! x!] p^x q^(n-x)
Where,
n = the
total number of test questions = 10
<span>x = the
total number of test questions to pass = >6</span>
p =
probability of success = 0.5
q =
probability of failure = 0.5
Given the
formula, let us calculate for the probabilities that the student will get at
least 6 correct questions by guessing.
P (6) = [10!
/ (4)! 6!] (0.5)^6 0.5^(4) = 0.205078
P (7) = [10!
/ (3)! 7!] (0.5)^7 0.5^(3) = 0.117188
P (8) = [10!
/ (2)! 8!] (0.5)^8 0.5^(2) = 0.043945
P (9) = [10!
/ (1)! 9!] (0.5)^9 0.5^(1) = 0.009766
P (10) = [10!
/ (0)! 10!] (0.5)^10 0.5^(0) = 0.000977
Total
Probability = 0.376953 = 0.38 = 38%
<span>There is a
38% chance the student will pass.</span>
Answer:
Step-by-step explanation:
<u>1.Find the LCM(Least Common Multiple).</u>
That would be 20.
<u>2.Multiply so all denominators are equal.</u>
<u>3. Add</u>
<u></u>
<u>4. Simplify</u>
<u></u>
This question is incomplete, the complete question is;
Suppose John is a high school statistics teacher who believes that watching many hours of TV leads to lower test scores. Immediately after giving the most recent test, he surveyed each of the 24 students in his class and asked them how many hours of TV they watched that week. He then matched each student's test grade with his or her survey response. After compiling the data, he used hours of TV watched to predict each student's test score. He found the least-squares regression line to be y" = -1.5x + 85.
He also calculated that the value of r, the correlation, was -0.61.
what is the correct value of the coefficient of determination R² and give a correct interpretation of its meaning
Answer:
Interpretation of coefficient of determination R² = 0.3721
R² = 0.3721, meaning 37.21% of the total variation in test scores can be explained by the least square regression line
Step-by-step explanation:
Given the data in the question;
the least square regression line is;
y" = -1.5x + 85
the correlation coefficient r = -0.61
Now, the coefficient of determination R² is square of correlation coefficient r
R² = -61²
R² = 0.3721
Not really sure what exactly you are asking, but maybe a bar graph?
