Jaclyn Reagan

  • jaclyn.reagan@live.longwood.edu

Work History

Work History

Stonepeak Ceramics
I was a packer/picker for a large tile factory.  This job required navigating through a large building while learning all of the different labeling and strategies of quickly locating certain types of tile.  Also, after locating a certain amount, I packed the merchandise to prepare it for shipping.  This job was a great way to acquire skills with new technology, working with a team and for managers and supervisors.  Also, with the amount of merchandise that the company sold, it was important to make minimal mistakes, so I learned quickly to hold myself accountable.  A very heavy load of safety strategies and regulations were also necessary to learn. Also, being punctual was very important.  
Jun 2012 - Aug 2012

Dollar General
cashier/merchandise stocker. 
This job required quickly learning the environment of the store.  It also required teamwork with colleagues and the manager.  Communication skills, being well mannered toward customers, punctuality, and carefully handling money. 
Mar 2010 - May 2012

Hardee's
Cashier/Cook.
Working at Hardee's required the following: people skills, time management, communication, ability to multitask, patience, learning safety strategies, memorizing an entire menu and how to prepare the food on the menu, and working well with fellow employees and working well for the managers. 

Education

Education

Aug 2012 - May 2016

Longwood University
Psychology was my major at Longwood University.  
While attending Longwood as a psychology major, I was also a member of the women's basketball team.  Playing a division 1 sport while being a full-time student requires many skills that are valuable in the workplace: time management/punctuality, leadership skills, working well with a team, working efficiently under pressure and physical fatigue, and practice managing and overcoming an overwhelming lifestyle. 

References

Tessi Gilmer        (931)-200-0440
I volunteered as a secretary at Mrs. Gilmer's Heating and Cooling shop.  Also, I babysat her 3 sons for the length of a summer. This developed office skills, and it displays that I am someone that can be trusted with the well-being of his/her children throughout a week. 

Bill Reinson         (804)-921-7664
College basketball coach.
This is one of the many coaches that I have played for in my life, but he has seen the transformation in me on the court, in the classroom, and in life in general.

Maya Ozery         (305)-781-8886
Academic advisor/coach
Ms. Ozery was a vital resource for me while attending Longwood University as a student athlete.  She has been acquired with the knowledge of my highest skills, but also has assisted me in transforming my weaknesses into strengths.  

Michelle Smith   (931)-200-6171
International Logistics Manager
Mrs. Smith is employed by Stonepeak Ceramics.  She was able to view my work ethic and skills on the job.  Also, I was an unofficial mentor for her twelve-year-old daughter. 


Portfolio

SPSS BASICS         

Use value labels to use words in place of numbers.

Use d commonly for Likert scales

In variable view, locate the variable column.            

Click the right side of the box you wish to create labels for.

Value is the original number.

Label is the word that you want.

Do not have to be in a specific order.

 

Click “OK”

Go to data view

Click “Value Labels”

 

 

 

Excluding Cases

Use to remove if we do not want it in our specific analysis.

Used if you want to exclude outliers.

Go to “Data View”

Highlight “data”

Click “select cases…”

Click “if condition is satisfied”

 

Next, click “If”

Write formula in box in which you want to KEEP in your analysis, NOT what you want to exclude.

Click “continue”

Click “paste” for sytanx

Highlight and click the green “play” button

Cases are excluded. This is apparent by looking at the “data view”, which displays slashes through the cases that have been excluded.

To include cases, go back to “select cases”, and click the “all cases”

This removes the slashes, which indicates that the cases have been included.

 

Sort cases

Used to sort them in preferred order.

Highlight “data”

Click “sort cases”

Arrow over

 

 

Transforming Data

If we want to take a variable and transform it into a different variable.

Highlight “transform”

Click “recode into different variables”

                                

Arrow over variable

     When choosing the name, do not include spaces because it will be a new column

 

Click “old and new values”

For old value, type it in exactly as it is in the data set.

When using a word, check “output variables are strings”

 

 

Click “continue”

 

 

Reverse Coding

Code scales back to their original state.

Highlight “transform”

Click “recode into diff. variables”

Arrow over variables

Type new column name

Click “change”

 

 

 

 

                Descriptive vs inferential data

                Descriptive- gives descriptive without applying to the population

                Inferential- tries to obtain an accurate sample to represent the population

                Measurement scales

                Nominal- categorical data

                Ordinal – numbers of order but not an equal distance between them

                Interval- order of numbers that are equal in distance but do not have an absolute zero

                Ratio – order of number that are equal in distance but have an absolute zero

                Descriptive Stats

                Mean- The average of scores or data

                Variability

                Deviation Score- how far score is away from the mean  

                Standard deviation – average distance of all scores from the mean sample

                population

                Sum of Squares = addition of all squared sums

                Variance- shows difference between a sample or population

                Z- scores

                Transform normally distributed variables into standard normal distribution

                Hypothesis

                Independent Variable (IV)- what is manipulated; either causes or does not cause a change

                Dependent Variable (DV)- the variable that will be measured

                Operational DV- how DV is measured

                Null Hypothesis – The IV will not Change the DV

                H0 = X̅1 = X̅2

                Alternative Hypothesis- The IV will change the DV- H1 = X̅1 ≠ X̅2

                Types of error

                -Type 1 – False positive

                -Type 2 – False negative

                -Alpha Level α- The chance of type 1 error

                -Chosen arbitrarily

                -.05 and .01 are most common

                Statistical Power

                -Increases the chances of rejecting null

                -Sample size increase

                -Higher alpha level

                -Lower variability

                -One tail testing

Symbols

                Σ= sum of squares

                s = sample

                σ = population

                α= alpha level or chance of type 1 error