Use the data set provided ibelow
1. Complete the full hypothesis testing procedure to determine if students at TCC watch less television than Americans in general. Use the fact that Americans watch 5.5 hours of television per day with a standard deviation of 1 hour per day. Include the following in your report:
a) Hypotheses using correct notation (2 points)
b) type of test (left, right, two-tailed) (1 point), distribution used (normal or t) (1 point), reasons why (2 points)
c) level of significance, choose one based on how serious the study is (2 points)
d) Sample statistics (sample size and sample mean or sample proportion) (2 points)
e) P-Value (2 point) (Round answer to four decimal places)
f) Interpretation of P-value (Use Definition of P-Value but be specific to this context) (1 point)
g) Drawing or graph of P-value. (2 points)
h) Decision (2 point)
i) Conclusion in complete sentences. (3 points)

datt ( number of hours of TV watched per day

4 5 2 2 0.5 2.5 1 2 3.5 6 1.5 2 1 6.5 7 3 3 3 1 1.5 4 6.5 3 2 4 1 2 2 2.5

7 1 5 1 2 3 5 7 1 4 6 1.5 2 2 2 2 2 0.5 2 5 4 2 1 2.5 6 2.5 1 4 4

Adipose tissue can be a source of fatty acids. The statements listed on the left describe the steps involved in fatty acid release from adipose. Put the statements in the correct order using 1 as the first step through 6 for the last step. Choose the numbers 1 through 6 in the drop-down menu on the right.

Group of answer choices

protein kinase activation

      [ Choose ]            1            3            6            5            4            2      

cAMP production

      [ Choose ]            1            3            6            5            4            2      

triacylglycerol lipase activation

      [ Choose ]            1            3            6            5            4            2      

fatty acid binding to serum albumin

      [ Choose ]            1            3            6            5            4            2      

hormone binding to receptor

      [ Choose ]            1            3            6            5            4            2      

adenylyl cyclase activation

      [ Choose ]            1            3            6            5            4            2      

You are given an array of arrays a. Your task is to group the arrays a[i] by their mean values, so that arrays with equal mean values are in the same group, and arrays with different mean values are in different groups.

Each group should contain a set of indices (i, j, etc), such that the corresponding arrays (a[i], a[j], etc) all have the same mean. Return the set of groups as an array of arrays, where the indices within each group are sorted in ascending order, and the groups are sorted in ascending order of their minimum element.

Example

• For

• a = [[3, 3, 4, 2],
•      [4, 4],
•      [4, 0, 3, 3],
•      [2, 3],
•      [3, 3, 3]]

the output should be

meanGroups(a) = [[0, 4],

                 [1],

                 [2, 3]]

• mean(a[0]) = (3 + 3 + 4 + 2) / 4 = 3;
• mean(a[1]) = (4 + 4) / 2 = 4;
• mean(a[2]) = (4 + 0 + 3 + 3) / 4 = 2.5;
• mean(a[3]) = (2 + 3) / 2 = 2.5;
• mean(a[4]) = (3 + 3 + 3) / 3 = 3.

There are three groups of means: those with mean 2.5, 3, and 4. And they form the following groups:

• Arrays with indices 0and 4 form a group with mean 3;
• Array with index 1 forms a group with mean 4;
• Arrays with indices 2and 3 form a group with mean 2.5.

Note that neither

meanGroups(a) = [[0, 4],

                 [2, 3],

                 [1]]

nor

meanGroups(a) = [[0, 4],

                 [1],

                 [3, 2]]

will be considered as a correct answer:

• • In the first case, the minimal element in the array at index 2 is 1, and it is less then the minimal element in the array at index 1, which is 2.
  • In the second case, the array at index 2 is not sorted in ascending order.
• For

• a = [[-5, 2, 3],
•      [0, 0],
•      [0],
•      [-100, 100]]

the output should be

meanGroups(a) = [[0, 1, 2, 3]]

The mean values of all of the arrays are 0, so all of them are in the same group.

Input/Output

• [execution time limit] 3 seconds (java)
• [input] array.array.integer a

An array of arrays of integers.

Guaranteed constraints:
1 ≤ a.length ≤ 100,
1 ≤ a[i].length ≤ 100,
-100 ≤ a[i][j] ≤ 100.

• [output] array.array.integer

An array of arrays, representing the groups of indices

C PROGRAMMING LANGUAGE

PROBLEM TITLE : ARRAY

usually, if people want to input number into an array, they will put it from index 0 until N - 1 using for. But, Bibi is bored to code like that. So, she didin't want to input the number that way.

So Bibi challenged you to make a program that will read a sequence (represent index) that she made, then input the number to an array but input it with the same sequence as sequence that Bibi gave.

Format Input

The first line represent integer N the size of Bibi's Array. The next line consist N integers Ai represent the sequence that Bibi want, it is guaranteed that the number is distinct. The next line consist N integers represent the value that she want to put inside array with index Ai.

Format Output

N integers represent the array that Bibi has starting from index 0.

Constraints

• 1 ≤ N ≤ 1, 000

• 0 ≤ Ai < N

Sample Input 1 (standard input)

5

0 1 2 3 4

1 2 3 4 5

Sample Output 1 (standard output)

1 2 3 4 5

Sample Input 2 (standard input)

5

4  3 2 1 0

1  2  3  4 5

Sample Output 2 (standard output)

5 4 3 2 1

sample Input 3 (standard input)

5

0 4 3 1 2

1 2 3 4 5

Sample Output 3 (standard output)

1 4 5 3 2

NOTES

• There isn’t any space after the last number.

• In the third sample Bibi want to input the number to array index 0 then 4 then 3 then 1 then 2

(MAKE THE COMPILER UNTIL SAMPLE 3)

Consider the natural log transformation (“ln” transformation) of variables labour cost (L_COST), and total number of rooms per hotel (Total_Rooms). 4.1 Use the least squares method to estimate the regression coefficients b0 and b1 for the log-linear model 4.2 State the regression equation 4.3 Give the interpretation of the regression coefficient b1. 4.4 Give an interpretation of the coefficient of determination R2. Also, test the significance of your model using the F-test. How, does the value of the coefficient of determination affect the outcome of the above test? Test whether a 1% increase of the total number of rooms per hotel can increase the labour cost by more than 0.20%? Use the 5% level of significance for this test.

Consider the natural log transformation (“ln” transformation) of variables labour cost (L_COST), and total number of rooms per hotel (Total_Rooms). 4.1 Use the least squares method to estimate the regression coefficients b0 and b1 for the log-linear model 4.2 State the regression equation 4.3 Give the interpretation of the regression coefficient b1. 4.4 Give an interpretation of the coefficient of determination R2. Also, test the significance of your model using the F-test. How, does the value of the coefficient of determination affect the outcome of the above test?Test whether a 1% increase of the total number of rooms per hotel can increase the labour cost by more than 0.20%? Use the 5% level of significance for this test.

Consider the natural ln transformation (“ln” transformation) of variables labour cost (L_COST), and total number of rooms per hotel (Total_Rooms).

4.1 Use the least squares method to estimate the regression coefficients b0 and b1 for the log-linear model

4.2 State the regression equation 4.3 Give the interpretation of the regression coefficient b1. Give an interpretation of the coefficient of determination R2. Also, test the significance of your model using the F-test. How, does the value of the coefficient of determination affect the outcome of the above test?

4.4.Test whether a 1% increase of the total number of rooms per hotel can increase the labour cost by more than 0.20%? Use the 5% level of significance for this test.

1.         What is the proportion of males who bullied others?  What is the proportion of females who bullied others?  Which gender (male or female) possessed a deeper involvement in bullying others?

An urban area consisting of four zones has the base-year trip matrix shown below.
The growth rates for the origin and destination trips have been projected for a 25 years period.
Using Fratar's techniques, calculate the number of trip interchanges in the horizon year.
Do just two iterations.

GF = Growth Factors