Answer:
line dancing, square dancing, etc
Step-by-step explanation:
The second one should by right
Answer: 2 1/3
Explanation:
10 2/6 - 7 5/6
You can make both a fraction by multiplying the denominator by the whole number, and then adding the numerator to that number, and keeping the denominator the same. So, 10*6 = 60 and 60 + 2 = 62 and you keep the denominator as 6, which would make 62/6
7*6 = 42 and 42 + 5 = 47 so 7 5/6 becomes 47/6
10 2/6 is equivalent to 62/6
7 5/6 is equivalent to 47/6
This just makes it easier to look at.
Now you just work through the equation.
62/6 - 47/6 = 15/6
15/6 = 2 3/6 = 2 1/3
Answer:
1. True
2. False.
3. True.
Step-by-step explanation:
1. The total area within any continuous probability distribution is equal to 1.00: it is true because the maximum probability (value) is one (1), therefore, the total (maximum) area is also one (1).
<em>Hence, for continuous probability distribution: probability = area</em>.
2. For any continuous probability distribution, the probability, P(x), of any value of the random variable, X, can be computed: False because it has an infinite number of possible values, which can not be counted or uncountable.
<em>Hence, it cannot be computed. </em>
3. For any discrete probability distribution, the probability, P(x), of any value of the random variable, X, can be computed: True because it has a finite number of possible values, which are countable or can be counted.
<em>Hence, it can be computed. </em>
Answer:
0.0623 ± ( 2.056 )( 0.0224 ) can be used to compute a 95% confidence interval for the slope of the population regression line of y on x
Step-by-step explanation:
Given the data in the question;
sample size n = 28
slope of the least squares regression line of y on x or sample estimate = 0.0623
standard error = 0.0224
95% confidence interval
level of significance ∝ = 1 - 95% = 1 - 0.95 = 0.05
degree of freedom df = n - 2 = 28 - 2 = 26
∴ the equation will be;
⇒ sample estimate ± ( t-test) ( standard error )
⇒ sample estimate ± ( 
) ( standard error )
⇒ sample estimate ± ( 
) ( standard error )
⇒ sample estimate ± ( 
) ( standard error )
{ from t table; ( ) = 2.055529 = 2.056
so we substitute
⇒ 0.0623 ± ( 2.056 )( 0.0224 )
Therefore, 0.0623 ± ( 2.056 )( 0.0224 ) can be used to compute a 95% confidence interval for the slope of the population regression line of y on x
