statistics

 

Phase 1 What factors affect happiness ranking in the American states?

Reasons: 1) Healthy Life Expectancy, the longer lives making the higher happiness ranking of states.

2) Medical income: the medical Insurance and medical facilities are both important factors for happiness rank

3) Unemployment rate; the lowest unemployment rate will affect the happiness rank.

4) The pressure of working; whether people love their job or not, the requirement of education level for the job. The lowest pressure of working will making the higher happiness ranking of states.

phase 2 please read the direction carefully .

http://www.city-data.com/

the website will be help you if you need. please use variable which is from the same year.

phase 3 please read the direction carefully as well. there is one more research paper phase 3 for help .

let me know if you have any questions. thank you .

1 day agoATTACHMENTS 

Sheet

1

1 0 0 0

0.36

1 0 0 0

0.05

1 0 0 0

0 0 1 0

1

1

0

OR

OR

ID/OBS Name

Y = Cancer Rate

X = income

X: M= 1 F=

0

X: White

X Black

X = Hispanic

X: Region South

East

North

West

AL

0.12

45000

0.67

0.22

0.04

MS

0.36

52000

0.53

0.05

TN

36000

Maine

OR

Young

Smith

Jones

Patriots

Bears

Yankees

Amazon

Google

ExXon

S

tatistical Research Projects

Phase 2

In a general format, state the model. In other words, identify your dependent and independent variables. Your model must include at least 3 independent variables, but not to exceed 7 independent variables.

a.

E

XA

M

PLE: If your research question is: “ Does parental income and education influence BMI? “, then the dependent variable would be BMI and the independent variables would be parental education and parental income.

i.

The general model statement: BMI = f(parental education, parental income).

2b. Identify the source or sources of your data.

W

hen using cross-sectional data ALL data must be pulled from the same time period but can be pulled from different sources. Identify the source and time period for each data element.

2c. Data sets much have a minimum of 5

0

observations, but not to exceed

1

00 observations.

2d. Include a definition of each data element, data source, and period for which data element is captured.

F

or example: BMI = Body Mass Index, is measure by body mass divided by the square of the individual’s height. Data source: Health and Human Services,

www.hhs.gov

, fiscal year 2010, state level data.

Example #2: Parental income = is combined household annual income. Data Source:

www.bls.gov

, state level data for 2012.

IMPORTA

N

T: Your dependent variable cannot be binary, categorical/ranking, or strictly a discrete variable. Your dependent variable must be a continuous variable. Your independent variables can be all continuous or a mix of discrete and continuous. Your independent variables CANNOT be strictly discrete variables.

Submission of Phases I – II: Must be submitted in WORD format. The word document should be attached to your email. Do not send Phase I and II as part of the body of an email. As part of the Phase II submission include Phase I. Definition of variables (see Phase II ‘2b’) should include time period data is captured, explicit definition of variable measurement or how the variable will be transformed for inclusion in Phase IV. For example:

INCORRECT: Weight –‘ how much a person weighs.’

CORRECT: Weight – ‘weight as measured in pounds’, data source Center for Disease Control,

www.cdc.gov

, individual level data, 2010.

INCORRECT: Unemployment rate – ‘the unemployment rate’

CORRECT: Unemployment rate – ‘the number of people unemployed per 1000, data source Bureau of Labor Statistics, www.bls.gov, state level data 2011.

Transformed Variables (see Phase 3 for example): Categorical variables such as gender, race, color, manufacturing sector, team, geographic region, as examples, need to be transformed into quantitative variables. For example, gender is captured as M or F, this will need to be transformed into 0,1 variable.

Example: M = 0 and F = 1 or M =1 and F = 0. The definition should read if M then M = 0 and if F then F=1

Example: Let’s assume your data contains 4 geographic regions,

North

, South, East, and

West

then for Phase II you will need to define the states that comprise the North geographic region, similarly for east, west, and south. In Phase III, you will need to transform these variables into columns of 0,1 dummy variables. See examples below.

PHASE 3

Analysis of your research question requires data. There are three general sources of data; (1) survey, (2) historical data, and (3) experimental data.

b. Survey data is response data from questionnaires. Students can construct a survey and collect their own data for purposes of this project by PERMISSION OF THE INSTRUCTOR ONLY. Students wishing to use survey data must provide me a copy of the survey prior to data collection for review. There are issues of privacy and human subjects protection that must be considered with every survey.

c. Historical data – is largely collected by public and private institutions. There are numerous publically available data sources on the web:

i.

http://www.rfe.org/showCat.php?cat_id=2

ii.

http://www.bls.gov/data/

iii.

http://www.freefinancialdata.com/stocks/index-data/

iv.

http://www.census.gov/compendia/statab/

v.

http://www.healthdata.gov/

vi.

http://nces.ed.gov/

vii. www.city-data.com

d. Experimental data – data obtained from controlled experiments. Using experimental data is not recommended for the purposes of this project.

Identify your data source(s). Once the data source(s) has/have been identified, input the data into an excel spreadsheet. Your data set must contain minimum of 50 observations
. All data must be cross sectional data. Cross sectional data is defined as different observations within the same time period. Examples of an excel data set is provided below:

Example 1

Example 2

Submission of Phase III: Phase III must be submitted in EXCEL format. Attach Phase I-II in your submission. This allows me to verify the accuracy of your data and data format in terms of your Phase I-II statements and definitions. See examples provided earlier in the document as to how your data should be captured.

Excel CANNOT read alpha characters. All alpha characters must be transformed into 0,1 variables. See examples below.

Transformation of variables – geographic example provided above:

0

0

N

1

0

0

0

0

0

1

0

0

1

0

0

0

0

0

1

S

0

0

0

1

E

0

1

0

0

Geographic Region

North

East

West

South

N

1

0

W

E

S

Transformation Example: For Individual level

Race

Variable

White

1

0

0

0

White

1

0

0

0

0

0

0

1

African American

0

1

0

0

0

0

1

0

African American

0

1

0

0

White

1

0

0

0

Race				White			African American	Hispanic	Asian
Asian
Hispanic

Transformation Example: Individual Level

Gender

Variable

1

0

F

0

M

1

Gender	Gender Binary m= 1 f = 0
	M
	F

Transformation Example:

National

Football Conference – American and National

League

1

0

American

1

American

1

League	American = 1 National = 0
		American
National

CompanyEarn/Share %GrowthNet IncomeRevenue%GrowthRevenueAnnual%ReturnStkPrice %Change

4Kids Entertainment31232.210077.9201-8

RF Micro Devices17955.9129325.116478

Siebel Systems190166.21171171.2173406

Network Appliance11573.880579.3224432

Source Information Mgmt.11211.212590.974-26

Salton16183.471795.99038

Zomax8830.3115238.49235

12 Technologies9658.471750.5138711

Diamond Tech Partners30016.250136.2133472

Stericycle76015.372186.74473

HomePrice $KSize sq feetNumber of BathroomsNicenessPool? yes=1; no=0

1260.926662.570

2337.334183.561

3268.429452.051

4242.229422.531

5255.227983.031

6205.722102.520

7249.522092.070