Business 205

Review

Part of a Business ProposalLiterature Reviews

Preview

Hypothesis WritingZ-scoresZ-testsInterpretations

Variables: IV, DV

IVs Cause In an experiment you manipulate the amount given

in each treatment 5 hours of sunlight 3 hours of sunlight 1 hour of sunlight

DVs What you are measuring; the effect

Darkness of tan

Causation

Some variable directly impacts another variable.

X Y

Example: X = Drinking alcohol

Y = Speech impairment

Hypotheses

Prediction about the relationship between variables (between IVs and DVs).

Makes a prediction about how the manipulation of the IV will affect the DV.

Example: Eating lots of chocolate will cause an upset

stomach.

Null Hypotheses

All other conditions that could occur other than that you predicted in your hypothesis

Example:Eating lots of chocolate will not cause an

upset stomach.

Types of Hypotheses

One-tailed – shows directionGreater, less, more, increases, decreases

Two-tailed – no direction is givenAffects, causes, inflicts

General “formula” for hypotheses

(Direction of ) IV does something to (direction of ) DV

IV: Sun exposure

DV: Skin cancer

Direction of IV: Increase

IV: Drinking alcohol

Direction of DV: Lowers

DV: Math scores

Mathematical Hypotheses

Symbolical showing of hypothesesUses >, <, ≤, ≥, =, ≠

Ma < Mp

Ma > Mp

Hypotheses

Hypothesis for 1-tailed HA: As a result of the XYZ company employee

training program, there will be a significant decrease in employee absenteeism.

• HA: Mean < Population Mean

Null Hypothesis for 1-tailed HO: As a result of the XYZ company employee

training program, there will either be no significant difference in employee absenteeism or there will be a significant increase. Ho: Mean ≥ Population Mean

Hypotheses: One-Tailed

If X (independent variable) then Y (dependent variable)

HA: As a result of the XYZ company employee training program, there will be a significant decrease in employee absenteeism.

Hypotheses

Hypothesis for 2-tailed HA: As a result of 300mg./day of the ABC drug, there will be a

significant difference in depression. HA: Mean ≠ Population mean

Null Hypothesis for 2-tailed HO: As a result of 300mg./day of the ABC drug, there will be no

significant difference in depression.

HO: Mean = Population mean

Hypotheses: Two-Tailed

If X (independent variable) then Y (dependent variable)

HA: As a result of 300mg./day of the ABC drug, there will be a significant difference in depression.

Types of Relationships

positive relationship--IV , DV

negative relationship--IV , DV

IV , DV

Scenario I

A manager at McDonalds thinks that Americans like large food portions therefore, the manager wants to know if increasing the size of French fries will affect sales. IV:DV:1 or 2-tailed:

Scenario I

Hypothesis

Mathematical Hypothesis

Null Hypothesis

Mathematical Null Hypothesis

Scenario I Distribution

Scenario II

A manager at McDonalds thinks that Americans like large food portions therefore, the manager wants to know if increasing the size of French fries will increase sales. IV:DV:1 or 2-tailed:Relationship:

Scenario II Distribution

Milestone 3

Write 1 – 2 paragraphs leading in to your group’s hypothesis The paragraph(s) should be an internal summary

and is a transition into the hypothesis Final line of the paragraph is boiler-plated and reads

something as follows: …the following hypothesis is forwarded:

H1: whatever your hypothesis is….

Write at least 1 hypothesis

Scenario II

Hypothesis

Mathematical Hypothesis

Null Hypothesis

Mathematical Null Hypothesis

Zzzzzzzzz

Z-Scores:Standardized Scores

Z-distributionNormally distributed z-scores whose mean

= 0 and SD = 1

Z-Scores (z)

Specifically defines how far away the raw score is from the mean.

z = (X – M)

SD

1. Find the mean (M)

2. Find the standard deviation (SD)

Z-Score Example

On a normal distribution of college student’s weight, with a mean of 140 lbs and a standard deviation of 22.0, what is the z-score for those who weigh 150 lbs?

z = (X – M) = (150-140)

SD 22.0

= .45

Z-Score Example

On a normal distribution of employee job satisfaction, with a mean of 3.04 and a standard deviation of 1.02, what is the z-score for those who had a job satisfaction level of:2.84 and 3.86

z = (X – M)

SD

Z-Test

When you want to compare your sample mean to a larger population

Can only conclude if your sample differs from that of the population.

Causes: sampling error, not a random sample, not representative of the population…

Z-Test

M = sample mean,

= population mean

SD = standard deviation

n = sample size n

SD) - (M

Z

Critical Values for Z-tests

One-tailed hypotheses (directional)

Critical Values for Z-tests

Two-tailed hypotheses (non-directional)

Z-test Example

You want to know if this section of BUS 205, with 25 students, differs from that of all BUS 205 classes this fall. The class mean on the exam was a 75 and the mean for all BUS 205 classes was an 83. The SD for all BUS classes was 2.

n

SD) - (M

Z

Z-test Example

Sample Mean = 75 Pop Mean = 83 SD = 2 n = 25 Zcrit = ±1.96

Z = -20.00 You can claim that your

sample differs from the population. You cannot claim in which direction!

25

23)8 - (75

Z

Z-test Example II

You want to know if the ladies at Macy’s Tucson Mall are more satisfied with overall store service as all other ladies who shop in Macy’s in the US. The sample of 12 women had a satisfaction mean of 3.8 and the mean for all those tested was a 4.2. The SD for all those tested was .96.

What is your hypothesis?

Sample Mean = 3.8 Pop Mean = 4.2 SD = .96 n = 12 Zcrit = + 1.645

Z = - 1.44

12

.964.2)-.83(

Z

Zcrit = + 1.645

Z = - 1.44

12

.964.2)-.83(

Z

+ 1.645