# Qnt561 entire course | Mathematics homework help

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I need help with the entire course starting with week2.  I need someone to help me to do the quizes and team assignments. I will do the participation.  Please reply with the price. For this week I need the 16 Questions MyMatj lab quiz, two team assigments.

Bank Supervisors experiment simulation

• Due Sep 19, 11:59 PM Estern time
• Not Submitted
• POINTS 1
• CASE week 1:
• Forty-eight male bank supervisors were each given the same personal file and asked to judge whether the person should be promoted to a branch manager job that was described as “routine”, or the file held and other applicants interviewed.
• The files were identical except that half of them showed that the file was that of a female and half showed that the file was that of a male.  Of the 24 “male files”, 21 were recommended for promotion. Of the 24 “female files”, 14 were recommended for promotion. [Rosen and Jerdee, 1974].
•

Simulation Experiment:

Components of the following simulation experiment are to be completed by individual students with the experiment as a whole to be completed by each learning team.

Individually remove all four aces from a deck of playing cards. There will now be 24 red cards in the deck, that will represent  “male” files, and 24 black cards that will represent “female” files. Alternatively, you may use 48 index cards, marking half with “M” and half with “F”. Shuffle the cards at least seven times and then cut them.

a. Count out the first 35 cards to represent the files recommended for promotion.

b. Each learning team: repeat the simulation with the cards until the team has a total of 100 simulations. With each simulation, record the number of “males” promoted. Post  the results of 100 simulations in the form of an empirical probability that 21 or more of the 35 recommended for promotion were male.

2nd assigment

HANDOUT University of Phoenix Material

Research Question Two Variable Handout

The research question (RQ) is developed from the business problem. Each variable is operationally defined so that reliable measurements may be taken. This DQ represents a managerial problem statement that needs to be put into a form that can be tested.

The independent and dependent variables are identified. The variables may be attribute (non-numeric) or numerical. More commonly, the dependent variable is the one that is numeric and measured. When there are two numeric variables, the IV generally precedes the DV.

Below are three cases.

Case 1: DV Numeric, IV Attribute

A manager asks why the productivity is different based on three daily shifts. To test this statement, we may first want to validate the observation. A hypothesis test will be decisive as to whether the productivity is different because of normal variation (by chance alone,) or whether there is statistical significance.

Productivity is abstract, so it is operationalized to be measure cases of product per hour.

A RQ may be as such:

RQ: Is there a difference in productivity (DV) based on the production shift (IV)?

Variables are productivity, numeric data, and shift, attribute data.

The hypothesis statements are the next step.

Ho: There is no difference in productivity (DV) based on the production shift (IV).

H1: There is a difference in productivity (DV) based on the production shift (IV).

Notice the alternate hypothesis, H1, is nearly identical to the RQ. Then notice the relationship between

H1 and Ho.

Case 2: DV Numeric, IV Numeric

A manager asks why a product’s profitability is inconsistent with sales.

Profitability is abstract, so it is operationalized to be measure Gross Profit (= Sales Revenue – Cost of

Goods Sold)

A RQ may be as such:

RQ: Is there a correlation in product profitability (DV) based on product sales (IV)?

Variables are profitability, numeric, and sales, numeric data.

The hypothesis statements are the next step.

Ho: There is no correlation in product profitability (DV) based on product sales (IV).

H1: There is a correlation in product profitability (DV) based on product sales (IV).

Case 3: DV Attribute, IV Attribute

A HR manager believes employees on the back shift are less satisfied than those on the day shift.

Satisfied is abstract, so it is operationalized to be Very Satisfied – Satisfied – In Different – Dissatisfied –Very Dissatisfied. Satisfaction has been operationalized by using a validate survey questionnaire.

A RQ may be as such:

RQ: Is there a relationship between employee satisfaction (DV) and specific shift (IV)?

Variables are satisfaction, attribute, and shift, attribute data.

The hypothesis statements are the next step.

Ho: There is no relationship between employee satisfaction (DV) and specific shift (IV).

H1: There is a relationship between employee satisfaction (DV) and specific shift (IV).

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Quiz: via Teamviewer

Pages (550 words)
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