Answer:
Step-by-step explanation:
10- -2 which gives you 12 cause the negatives make a positive.
-9 -0= -9
12 over -9 which simplifies to 4 over -3
Answer:
Thus percentile lies between 53.3% and 55.6 %
Step-by-step explanation:
First we arrange the data in ascending order . Then find the number of the values corresponding to the given value. Then equate it with the number of observations and x and then multiply it to get the percentile. n= P/100 *N
where n is the ordinal rank of the given value
N is the number of values in ascending order.
The data in ascending order is
0.1 0.2 0.2 0.2 0.3 0.6 0.6 0.6 0.7 0.8 0.8 0.8 0.9 1.3
1.5 1.7 1.9 2.2 2.3 2.3 2.6 2.8 3.3 3.5 5.5 6.1 6.4 6.9 7.5 7.9 8.3 9.8 10.1 11.8 11.9 12.1 12.3 12.7 12.9 13.8 13.8 14.6 14.7 14.8 27.5
Number of observation = 45
4.9 lies between 3.3 and 5.5
x*n = 24 observation x*n = 25 observation
x*45= 24 x*45= 25
x= 0.533 x= 0.556
Thus percentile lies between 53.3% and 55.6 %
This answer is not correct
<span>C. Use objects to model the problem. Take 8 pieces of play money. Take away 1 piece for the coffee and 2 pieces for the bagel.</span>
Answer:y=-5/3x+1
-5/3
1
Step-by-step explanation:you move the 5x to the right making the equation 3y=-5x + 3, then you divide everything by 3. You then find the other info by knowing y=mx+b which means m=slope and b = y intercept
Answer:
The dependent variable is the final grade in the course and is the vriable of interest on this case.
H0: 
H1: 
And if we reject the null hypothesis we can conclude that we have a significant relationship between the two variables analyzed.
Step-by-step explanation:
On this case w ehave the following linear model:

Where Y represent the final grade in the course and X the student's homework average. For this linear model the slope is given by
and the intercept is 
Which is the dependent variable, and why?
The dependent variable is the final grade in the course and is the vriable of interest on this case.
Based on the material taught in this course, which of the following is the most appropriate alternative hypothesis to use for resolving this question?
Since we conduct a regression the hypothesis of interest are:
H0: 
H1: 
And if we reject the null hypothesis we can conclude that we have a significant relationship between the two variables analyzed.