Answer:
-2
Step-by-step explanation:
To find the slope of the line you have to use the equation,
(y2-y1)/(x2-x1)
In this case it is, (-4-2)/7-4)
This simplifies to -2 and this is the slope of the line
Answer:
-8/5
hope this help!
5y + 1
â 4 + 7x â 20y
Let f(x, y) = 7x + 4 5y + 1 . Then fx(x, y) = ________
Answer:
Measures equal or lower than 19.94 inches are significantly low.
Measures equal or higher than 25.06 inches are significantly high.
Step-by-step explanation:
Problems of normally distributed samples can be solved using the z-score formula.
In a set with mean and standard deviation , the zscore of a measure X is given by:
The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.
In this problem, we have that:
Find the back-to-knee lengths separating significant values from those that are not significant.
Significantly low
In this exercise, a value is going to be to significantly low if it has a pvalue of 0.01 or less. So we have to find X when Z has a pvalue of 0.01. This is between and , so we use
Measures equal or lower than 19.94 inches are significantly low.
Significantly high
In this exercise, a value is going to be to significantly high if it has a pvalue of 0.99 or more. So we have to find X when Z has a pvalue of 0.99. This is . So:
Measures equal or higher than 25.06 inches are significantly high.
To find the separating back-to-knee lengths, we calculate the corresponding z-scores for the given probabilities. Using the standard normal distribution table, we find that the separating values are 24.78 inches for significantly high lengths and 20.22 inches for significantly low lengths.
To find the back-to-knee lengths separating significant values from those that are not significant, we need to calculate the z-scores corresponding to the given probabilities. For a value to be significantly high, we look for a z-score such that the area to its right is 0.01. Using the standard normal distribution table, we find that z = 2.33. Similarly, for a value to be significantly low, we look for a z-score such that the area to its left is 0.01. Again using the table, we find that z = -2.33. Converting these z-scores back to actual back-to-knee lengths, we can calculate the separating values as: 22.5 + (2.33 * 1.1) = 24.78 inches for significantly high lengths, and 22.5 - (2.33 * 1.1) = 20.22 inches for significantly low lengths.
#SPJ3
where y represents exam score (0 to 100 points), x1 represents the amount paid to a tutor (in dollars) in the week before the exam, x2 represents the number of hours of sleep in the week before the exam, and as represents number of study hours in the week before the exam. How many independent variables are included in this model?
a. 3
b. 2
c. 1
d. 4
Answer:
a. 3
Step-by-step explanation:
An independent variable is the variable that is changed in an experiment to test its effects on the dependent variable. i.e. inputs
A dependent variable is the variable being tested, measured or predicted in an experiment. I.e a outcome
In this case, the the effects of the amount tutors are paid a week before exam, the amount of sleep before exam and the number of study hours are input variables to determine or predict a students score in exam
The independent variables are;
x1 =represents the amount paid to a tutor (in dollars) in the week before the exam
x2 = represents the number of hours of sleep in the week before the exam
x3 = number of study hours in the week before the exam
The dependent variable is the exam score
B0, B1, B2,B3, B4 are coefficients
Answer:
Step-by-step explanation:
We would set up the hypothesis test. This is a test of a single population mean since we are dealing with mean
For the null hypothesis,
µ = 90
For the alternative hypothesis,
µ < 90
If drinking coffee just before going to sleep affects the amount of dream time, then the amount of dream time would be less than 90 minutes. It means that it is left tailed.
Since the number of samples is 28 and no population standard deviation is given, the distribution is a student's t.
Since n = 28,
Degrees of freedom, df = n - 1 = 28 - 1 = 27
t = (x - µ)/(s/√n)
Where
x = sample mean = 88
µ = population mean = 90
s = samples standard deviation = 9
t = (88 - 90)/(9/√28) = - 1.176
We would determine the p value using the t test calculator. It becomes
p = 0.124
Since alpha, 0.05 < than the p value, 0.124, then we would not reject the null hypothesis. Therefore, At a 5% level of significance, the sample data did
not show significant evidence that drinking coffee just before going to sleep affects the amount of dream time.