Directions: Use the Bivatiate Correlation function and the Options submenu to answer each of the questions based on the above scenario.

The superintendent has continued the examination of data by examining the relationship between attendance rate and percent of students eligible for free or reduced priced lunch. The district data used for the analysis are contained below.

School % Free or Reduced Attendance Rate 1 47.0 94.8 2 31.1 96.1 3 58.9 94.9 4 40.9 94.2 5 24.1 95.7 6 50.4 94.8 7 54.7 93.8 8 60.1 92.6 9 49.6 93.6 10 42.9 93.8 11 38.1 92.8

School % Free or Reduced Attendance Rate 12 27.2 99.7 13 58.4 93.4 14 52.4 93.6 15 58.4 94.6 16 64.9 93.0 17 75.5 92.3 18 30.6 95.1 19 79.4 92.8 20 67.3 92.6 21 56.7 95.5 22 74.7 91.8

1. What is the mean percent of students receiving free or reduced lunch? What is the mean attendance rate?

51.97 free or reduced

94.16 attendance

2. What are the standard deviations for the percent of students receiving free or reduced lunch and attendance rate?

15.68 free or reduced

1.71 attendance

3. State an appropriate null hypothesis for this analysis.

4. What is the value of the correlation coefficient?

5. Based on the value of the correlation coefficient, how would you classify the strength of this relationship?

6. Based on the information from the scenario, what is the appropriate value for the degrees of freedom?

7. What is the reported level of significance?

8. Present the results as they might appear in an article. This must include a table and narrative statement that reports and interprets the results of your analysis.

Note: The table must be created using your word processing program. Tables that are copied and pasted from SPSS are not acceptable.

QUESTION 1

Jason is applying for a job. A pre-employment assessment indicates that he is generally helpful, considerate, cooperative, and trusting of others. Jason has a high level of…

		Agreeableness
		Openness to experience
		Extraversion
		Conscientiousness

QUESTION 7

1. Julio is generally happy and content with his job. He enjoys his salary and gets along well with his coworkers. He is not energetic or enthusiastic about his work though. Julio is showing high _____________ and low _______________.

   	A.	Organizational commitment; job satisfaction
   	B.	Organizational citizenship; employee engagement
   	C.	Employee engagement; job satisfaction
   	D.	Job satisfaction; employee engagement

QUESTION 8

1. Suppose you are looking to hire engineers. ___________________ refer to “can do” or “competence”-related factors that influence their performance. ________________ refer to the “will do” or “character” factors that influence their performance.

   	A.	Conscientiousness and integrity; knowledge and skill in engineering
   	B.	Conscientiousness and integrity; extraversion and agreeableness
   	C.	Knowledge and skill in engineering; conscientiousness and integrity
   	D.	Knowledge and skill in engineering; intelligence

QUESTION 10

Charles stays at his job because he feels obligated. He would feel guilty about leaving, with all that his coworkers and supervisor have done for him. Which type of commitment is this demonstrating?

	A.	Affective commitment
	B.	Continuance commitment
	C.	Group commitment
	D.	Normative commitment

QUESTION 11

1. A teacher has discovered over a period of time that, even though her school has treated her well and she has a positive view of the school and the organization’s mission, she does not really like to teach and the task of teaching is not really for her. This is most likely to result in low levels of…

   	A.	Affective commitment
   	B.	Continuance commitment
   	C.	Normative commitment
   	D.	Job satisfaction

1. Suppose a random sample of 100 Utah families yields a total fertility rate (the average number of children born per woman) of 2.71. Given what the Central Limit Theorem tells us about the relationship between sample statistics and population parameters, we can assume the total fertility rate for all Utah families is

Exactly 2.71. No more, no less.

Less than 2.71, as the sampling distribution for the TFR is always negatively skewed

likely close to 2.71, though not necessarily EXACTLY 2.71

Far too high relative to the number of students our public education system can realistically support (this is NOT the correct answer)

2. Suppose you're interested in tracking Americans' church attendance. A sample of 900 Americans finds that 22 percent of respondents report attending church at least once per week. If this poll has a margin of error of plus/minus three percent, we can be fairly certain that the percentage of all Americans who attend church at least once per week falls between _______ percent and _______ percent.

Group of answer choices

19; 25

21.7; 22.3

16; 28

There's simply no way of knowing because everyone lies about how often they go to church (this is not the correct answer, although it's probably true).

3. Suppose weights of high school wrestlers are normally distributed with a mean of 145 pounds and a standard deviation of 15 pounds. Approximately what percent of wrestlers weigh between 135 and 150 pounds?

Group of answer choices

37.81 percent

74.75 percent

25.25 percent

0.3781 percent

4. Suppose weights of high school wrestlers are normally distributed with a mean of 145 pounds and a standard deviation of 15 pounds. What weight (approximately) corresponds with the 75^th percentile?

Group of answer choices

134.883

140.22

149.78

155.117

Previous info: Cost Is No Object is a car rental service that specializes in lending antique and luxury cars to clients on a short-term basis. A typical customer might rent a vintage convertible to transport out-of-town clients to a business meeting, or rent a luxury car to transport a wedding party. The service currently has three employees and ten vehicles that it rents.

Case Projects CH.4 Case: Cost Is No Object

In earlier chapters, you developed classes needed for Cost Is No Object—a car rental service that specializes in lending antique and luxury cars to clients on a short-term basis. The rental service produces computerized paychecks for its employees every week. Write a program that gets data for each of the following:  

An employee ID number

A first name

  A last name

A street address

A zip code

An hourly pay rate

Number of hours worked this week

An insurance plan code

Create an application that prompts the user for employee data; the application continues to accept data for new employees until the user enters 0 for an ID number to quit. While the ID number is not zero, prompt the user for a value for each field in turn. Any time the user enters an invalid value, continue to reprompt the user for the same data. Continue with the next data item only when the previous item is valid, as follows:

An employee ID must be between 100 and 999 inclusive.

A zip code must not be greater than 99999.

An hourly pay rate must be between $6.00 and $25.00 inclusive.

The number of hours worked in a week cannot be negative or more than 70.

An insurance plan code must be 1 or 2.

When all the needed data has been entered correctly for an employee, display a copy of all the data fields for the employee as well as the following:

Gross pay, calculated as hours worked times pay rate

Income tax, which is calculated as 15% of the gross pay if the gross pay is $400 or less; otherwise, it is 20% of the gross pay

An insurance premium, which is $60 for insurance plan code 1 and $100 for insurance plan code 2

Net pay, which is calculated as gross pay minus income tax, minus insurance premium; if the net pay is negative (the employee did not earn enough to cover the tax and insurance), then the net pay should be $0

1. A researcher claims that the mean rate of Infant mortality in the City of Chicago is below 9.3 %. Based on the data represented for the years 2005 – 2011, perform a hypothesis test to test his claim using a significance level of α= 0.10.

2.Would your conclusion change for question 1 if you used a significance level of α= 0.05? Explain.

Data:

community Area Name	Infant Mortality Rate
Rogers Park	6.4
West Ridge	5.1
Uptown	6.5
Lincoln Square	3.8
North Center	2.7
Lake View	2.2
Lincoln park	2.4
Near North Side	6.5
Edison Park	4.6
Norwood Park	4.4
Jefferson Park	8.3
Forest Glen	3.8
North Park	5.4
Albany Park	4.9
Portage Park	4.7
Irving Park	5.3
Dunning	4.9
Montclaire	4.6
Belmont Cragin	5.6
Hermosa	9.3
Avondale	5.7
Logan Square	4.3
Humboldt Park	9.8
West town	5.1
Austin	13.3
West Garfield Park	19
East Garfield Park	11
Near West side	9.1
North Lawndale	14.1
South Lawndale	5.9
Lower West Side	5.4
Loop	5.7
Near South Side	4.8
Armour Square	1.5
Douglas	13.4
Oakland	8.2
Fuller Park	22.6
Grand Boulevard	12.1
Kenwood	8.9
Washington Park	19.3
Hyde Park	10.4
Woodlawn	11.5
South Shore	11.4
Chatham	10.9
Avalon Park	11.4
South Chicago	17.7
Burnside	13
Calumet Heights	13.9
Roseland	9.6
Pullman	13.6
South Deering	11.8
East Side	3.7
West Pullman	11.9
Riverdale	8.7
Hegewisch	8.4
Garfield Ridge	4.5
Archer Heights	5.2
Brighton Park	5.9
McKinley Park	7.3
Bridgeport	8
New City	7.9
West Elsdon	8.1
Gage Park	5.4
Clearing	6.7
West Lawn	8.4
Chicago Lawn	11.1
West Englewood	13.3
Englewood	13.4
Greater Grand Crossing	14.2
Ashburn	10.2
Auburn Gresham	15.6
Beverly	10
Washington Heights	11.2
Mount Greenwood	3.3
Morgan Park	13.1
O'Hare	2
Edgewater	6.9

Please show work. Thank you :)

Back in Boston, Steve has been busy creating and managing his new company, Teton Mountaineering (TM), which is based out of a small town in Wyoming. In the process of doing so, TM has acquired various types of assets. Below is a list of assets acquired during 2016: Exhibit 10-8 (Use MACRS Table 1, Table 2, Table 3, Table 4 and Table 5.) (Round intermediate calculations and final answer to the nearest whole dollar amount.)

Asset Cost Date Placed in Service Office furniture $ 10,000 02/03/2016

Machinery 560,000 07/22/2016

Used delivery truck* 15,000 08/17/2016

* Not considered a luxury automobile, thus not subject to the luxury automobile limitations. During 2016, TM had huge success (and had no §179 limitations) and Steve acquired more assets the next year to increase its production capacity.

These are the assets acquired during 2017: Date Placed Asset Cost in

Service Computers & info. system $ 40,000 03/31/2017

Luxury auto† 80,000 05/26/2017

Assembly equipment 475,000 08/15/2017

Storage building 400,000 11/13/2017

†Used 100% for business purposes.

TM generated taxable income in 2017 of $732,500 for purposes of computing the §179 expense.

a. Compute the maximum 2016 depreciation deductions including §179 expense (ignoring bonus depreciation).

b. Compute the maximum 2017 depreciation deductions including §179 expense (ignoring bonus depreciation).

c. Compute the maximum 2017 depreciation deductions including §179 expense, but now assume that Steve would like to take bonus depreciation on the 2017 assets.

d. Ignoring part c, now assume that during 2017, Steve decides to buy a competitor’s assets for a purchase price of $350,000.

Compute the maximum 2017 cost recovery including §179 expense (ignoring bonus depreciation). Steve purchased the following assets for the lump-sum purchase price. Date Placed Asset Cost in Service Inventory $ 20,000 09/15/2017

Office furniture 30,000 09/15/2017

Machinery 50,000 09/15/2017

Patent 98,000 09/15/2017

Goodwill 2,000 09/15/2017

Building 130,000 09/15/2017

Land 20,000 09/15/2017

Back in Boston, Steve has been busy creating and managing his new company, Teton Mountaineering (TM), which is based out of a small town in Wyoming. In the process of doing so, TM has acquired various types of assets. Below is a list of assets acquired during 2015: (Use MACRS Table 1, Table 2, Table 3, Table 4 and Table 5.) (Round intermediate calculations and final answer to the nearest whole dollar amount.)

Asset	Cost		Date Placed in Service
Office furniture	$	10,000	02/03/2015
Machinery		560,000	07/22/2015
Used delivery truck*		15,000	08/17/2015

* Not considered a luxury automobile, thus not subject to the luxury automobile limitations.

During 2015, TM had huge success (and had no §179 limitations) and Steve acquired more assets the next year to increase its production capacity. These are the assets acquired during 2016:

			Date Placed
Asset	Cost		in Service
Computers & info. system	$	40,000	03/31/2016
Luxury auto†		80,000	05/26/2016
Assembly equipment		475,000	08/15/2016
Storage building		400,000	11/13/2016
†Used 100% for business purposes. TM generated taxable income in 2016 before any §179 expense of $732,500. a. Compute the maximum 2015 depreciation deductions including §179 expense (ignoring bonus depreciation). b. Compute the maximum 2016 depreciation deductions including §179 expense (ignoring bonus depreciation). c. Compute the maximum 2016 depreciation deductions including §179 expense, but now assume that Steve would like to take bonus depreciation on the 2016 assets. d. Ignoring part (c), now assume that during 2016, Steve decides to buy a competitor’s assets for a purchase price of $350,000. Compute the maximum 2016 cost recovery including §179 expense (ignoring bonus depreciation). Steve purchased the following assets for the lump-sum purchase price. Date Placed Asset Cost in Service Inventory $ 20,000 09/15/2016 Office furniture 30,000 09/15/2016 Machinery 50,000 09/15/2016 Patent 98,000 09/15/2016 Goodwill 2,000 09/15/2016 Building 130,000 09/15/2016 Land 20,000 09/15/2016

Back in Boston, Steve has been busy creating and managing his new company, Teton Mountaineering (TM), which is based out of a small town in Wyoming. In the process of doing so, TM has acquired various types of assets. Below is a list of assets acquired during 2016: Exhibit 10-8 (Use MACRS Table 1, Table 2, Table 3, Table 4 and Table 5.) (Round intermediate calculations and final answer to the nearest whole dollar amount.)

Asset	Cost		Date Placed in Service
Office furniture	$	10,000	02/03/2016
Machinery		560,000	07/22/2016
Used delivery truck*		15,000	08/17/2016

* Not considered a luxury automobile, thus not subject to the luxury automobile limitations.

During 2016, TM had huge success (and had no §179 limitations) and Steve acquired more assets the next year to increase its production capacity. These are the assets acquired during 2017:

			Date Placed
Asset	Cost		in Service
Computers & info. system	$	40,000	03/31/2017
Luxury auto†		80,000	05/26/2017
Assembly equipment		475,000	08/15/2017
Storage building		400,000	11/13/2017

^†Used 100% for business purposes.

TM generated taxable income in 2017 of $732,500 for purposes of computing the §179 expense.

a. Compute the maximum 2016 depreciation deductions including §179 expense (ignoring bonus depreciation).

b. Compute the maximum 2017 depreciation deductions including §179 expense (ignoring bonus depreciation).

c. Compute the maximum 2017 depreciation deductions including §179 expense, but now assume that Steve would like to take bonus depreciation on the 2017 assets.

d. Ignoring part c, now assume that during 2017, Steve decides to buy a competitor’s assets for a purchase price of $350,000. Compute the maximum 2017 cost recovery including §179 expense (ignoring bonus depreciation). Steve purchased the following assets for the lump-sum purchase price.

			Date Placed
Asset	Cost		in Service
Inventory	$	20,000	09/15/2017
Office furniture		30,000	09/15/2017
Machinery		50,000	09/15/2017
Patent		98,000	09/15/2017
Goodwill		2,000	09/15/2017
Building		130,000	09/15/2017
Land		20,000	09/15/2017

Can someone please complete the following code(Java). The stuff in comments are the things you need to look at and code that

package mini2;

import static mini2.State.*;

/**

* Utility class containing the key algorithms for moves in the

* a yet-to-be-determined game.

*/

public class PearlUtil

{

private PearlUtil()

{

// disable instantiation

}

/**

   * Replaces all PEARL states with EMPTY state between indices

   * start and end, inclusive.

   * @param states

   * any array of States

   * @param start

   * starting index, inclusive

   * @param end

   * ending index, inclusive

   */

public static void collectPearls(State[] states, int start, int end)

{

// TODO

}

  

/**

   * Returns the index of the rightmost movable block that is at or

   * to the left of the given index start. Returns -1 if

   * there is no movable block at start or to the left.

   * @param states

   * array of State objects

   * @param start

   * starting index for searching

   * @return

   * index of first movable block encountered when searching towards

   * the left, starting from the given starting index; returns -1 if there

   * is no movable block found

   */

public static int findRightmostMovableBlock(State[] states, int start)

{

// TODO

return 0;

}

  

  

/**

   * Creates a state array from a string description, using the character

   * representations defined by State.getValue. (For invalid

   * characters, the corresponding State will be null, as determined by

   * State.getValue.)

   * Spaces in the given string are ignored; that is, the length of the returned

   * array is the number of non-space characters in the given string.

   * @param text

   * given string

   * @return

   * State array constructed from the string

   */

public static State[] createFromString(String text)

{

// TODO

return null;

}

  

/**

   * Determines whether the given state sequence is valid for the moveBlocks

   * method. A state sequence is valid for moveBlocks if

   *

   *

• its length is at least 2, and

     *

• the first state is EMPTY, OPEN_GATE, or PORTAL, and

     *

• it contains exactly one boundary state, which is the last element

     * of the array

     *

   * Boundary states are defined by the method State.isBoundary, and

   * are defined differently based on whether there is any movable block in the array.

   * @param states

   * any array of States

   * @return

   * true if the array is a valid state sequence, false otherwise

   */

public static boolean isValidForMoveBlocks(State[] states)

{

// TODO

return false;

}

  

/**

   * Updates the given state sequence to be consistent with shifting the

   * "player" to the right as far as possible. The starting position of the player

   * is always index 0. The state sequence is assumed to be valid

   * for movePlayer, which means that the sequence could have been

   * obtained by applying moveBlocks to a sequence that was valid for

   * moveBlocks. That is, the validity condition is the same as for moveBlocks,

   * except that

   *

   *

• all movable blocks, if any, are as far to the right as possible, and

     *

• the last element may be OPEN_GATE or PORTAL, even if there are

     * no movable blocks

     *

   *

   * The player's new index, returned by the method, will be one of the following:

   *

   *

• if the array contains any movable blocks, the new index is just before the

     * first movable block in the array;

     *

• otherwise, if the very last element of the array is SPIKES_ALL, the new index is

     * the last position in the array;

     *

• otherwise, the new index is the next-to-last position of the array.

     *

   * Note the last state of the array is always treated as a boundary for the

   * player, even if it is OPEN_GATE or PORTAL.

   * All pearls in the sequence are changed to EMPTY and any open gates passed

   * by the player are changed to CLOSED_GATE by this method. (If the player's new index

   * is on an open gate, its state remains OPEN_GATE.)

   * @param states

   * a valid state sequence

   * @return

   * the player's new index

   */

public static int movePlayer(State[] states)

{

// TODO

return 0;

}

/**

   * Updates the given state sequence to be consistent with shifting all movable

   * blocks as far to the right as possible, replacing their previous positions

   * with EMPTY. Adjacent movable blocks

   * with opposite parity are "merged" from the right and removed. The

   * given array is assumed to be valid for moveBlocks in the sense of

   * the method validForMoveBlocks. If a movable block moves over a pearl

   * (whether or not the block is subsequently removed

   * due to merging with an adjacent block) then the pearl is also replaced with EMPTY.

   *

   * Note that merging is logically done from the right.

   * For example, given a cell sequence represented by ".+-+#", the resulting cell sequence

   * would be "...+#", where indices 2 and 3 as move to index 3 and disappear

   * and position 1 is moved to index 3.

   * @param states

   * a valid state sequence

   */

public static void moveBlocks(State[] states)

{

// TODO

}

}

Here's the class where you can check your code

package mini2;

/**
* Possible cell states for a certain puzzle game.
*/
public enum State
{
// WARNING: if we change these, be sure to update the TEXT array too!
EMPTY,
WALL,
PEARL,
OPEN_GATE,
CLOSED_GATE,
MOVABLE_POS,
MOVABLE_NEG,
SPIKES_LEFT,
SPIKES_RIGHT,
SPIKES_DOWN,
SPIKES_UP,
SPIKES_ALL,
PORTAL;
  

public static boolean isMovable(State s)
{
return s == MOVABLE_POS || s == MOVABLE_NEG;
}
  

public static boolean canMerge(State s1, State s2)
{
return s1 == MOVABLE_POS && s2 == MOVABLE_NEG ||
s2 == MOVABLE_POS && s1 == MOVABLE_NEG;
}
  

  
public static boolean isBoundary(State s, boolean containsMovable)
{
if (!containsMovable)
{
return s == CLOSED_GATE ||
s == SPIKES_LEFT ||
s == SPIKES_RIGHT ||
s == SPIKES_DOWN ||
s == SPIKES_UP ||
s == SPIKES_ALL ||
s == WALL;
}
else
{
return s == CLOSED_GATE ||
s == SPIKES_LEFT ||
s == SPIKES_RIGHT ||
s == SPIKES_DOWN ||
s == SPIKES_UP ||
s == SPIKES_ALL ||
s == WALL ||

  
s == OPEN_GATE ||
s == PORTAL;
}
}
  

public static final char[] TEXT = {
'.', // EMPTY,
'#', // WALL,
'@', // PEARL,
'o', // OPEN_GATE,
'x', // CLOSED_GATE,
'+', // MOVABLE_POS,
'-', // MOVABLE_NEG,
'<', // SPIKES_LEFT,
'>', // SPIKES_RIGHT,
'v', // SPIKES_DOWN,
'^', // SPIKES_UP,
'*', // SPIKES_ALL,
'O'// PORTAL;
};
  

public static final char NULL_CHAR = 'n';
  

public static char getChar(State s)
{
if (s == null)
{
return NULL_CHAR;
}
else
{
return TEXT[s.ordinal()];
}
}
  
  
public static State getValue(char c)
{
int i;
for (i = 0; i < TEXT.length; ++i)
{
if (TEXT[i] == c)
{
break;
}
}
if (i < TEXT.length)
{
return State.values()[i];
}
else if (c >= 'A' && c <= 'Z')
{
return State.PORTAL;
}
else return null;
}
  
  
public static String toString(State[] arr)
{
return toString(arr, true);
}
  
  
public static String toString(State[] arr, boolean addSpaces)
{
String text = "";
for (int col = 0; col < arr.length; ++col)
{
State s = arr[col];
char ch = getChar(s);
text += ch;
if (addSpaces && col < arr.length - 1)
{
text += " ";
}
}
return text;
}

  
}