In the first part of this week, you will work on data organization.? Data organization is a very important skill to learn. There is no right or wrong

 

In the first part of this week, you will work on data organization.  Data organization is a very important skill to learn. There is no right or wrong way to do this- however, the way that I am teaching you here is a good one and will benefit you in the future.  There is no room for error in research and this is especially true in data handling.  This week you will give it a try.

Do the following:

  • Download the Datasheet.
  • Watch these tutorials on the assignment and data spreadsheet here: https://youtu.be/5vOuwVBztog  and https://www.youtube.com/watch?v=s4Dnf5pO5Vw
  • This is important to watch along with the spreadsheet so you can follow along.  You will be provided with important details.  The tutorial is on a different set of data and reports that the names would be false as well as some data.  Your dataset may or may not be real – If you notice names of individuals not in your class, simply 'pretend' they are students in the class. I often add additional participants to make. the analysis work.  Please DO follow along. 
  • Notice when you open the Excel spreadsheet you see 3 tabs. Write clear column headers. Use colors and borders for clarity.
    • The first two tabs include the Raw Data (the data as it was saved from the experiment). This is not organized for analysis. Check for errors in participation, order (typically you organize data alphabetically or by participant number) etc. Make sure to note any errors/ exclusions on the Code Key information sheet. 
    • On the third tab, DATA, organize the spreadsheet so that the extra information is deleted and the spreadsheet has clear columns. 
    • The fourth tab Code Key is where you will define all of the abbreviations, titles, and information on calculations. You also can include notes here. The purpose is so that if you revisit this data in a year you will still be clear on exactly what the numbers mean and what you did. 
    • Dummy Code when needed. For example, Gender so that 1 = male and 2 = female;  Dummy Code Phase (Phase 1 = 1 and Phase 2 = 2) etc.
  • Clean and separate each task on the Raw Data sheets before moving them to the DATA sheet. 
    • Be careful to note which task was with which phase and if it had music (for example Task A, Phase 1, no music, and Task B, Phase 2, music).
    • Highlight the data you want to move, then paste the data in the right space for that task. Do this for each participant, each phase/task.
    • Make sure to note ID and gender.
    • Note that the response times are in milliseconds.  When you present these in results you will likely want to change these to seconds or minutes.
  • Calculate the Total Response Time for Phase A and Phase B for each task by the participant. The formula to sum response time is  =sum(highlight cells for that phase and task). 
  • Calculate the Total Response Time the tasks with Music tasks without music. The formula for tasks with no music is  = SUM (Total Phase 1 TASK A, Total Phase 2 Task B).   The formula for tasks with music is =SUM(Total Phase 1 Task B, Total Phase 2 Task A).  
  • Calculate the  Response Time difference for each participant for the tasks with Music and without Music by subtracting the Total Response Time No Music from the Total Response Time Music  (Note- You can do this in either direction as long as you understand what the difference means- is there an increase or decrease in response time?) .   
  • Calculate the Response Time Difference between Classical and Rock music. The formula is SUM(Total Phase 1 Task B – Total Phase 2 Task A). 
  • On the third tab, Code Key, write a coding key that should include all definitions of variables, calculation information, and coding information. Be clear enough that if you look back in two years, you know exactly what you did and can understand the data page.

RSM802 Week 7 Lab Instructions

Methodology

IMPORTANT: Follow the template below exactly. The text in blue are instructions and should NOT be included in your assignment. Please read all instructions carefully.

Hypothesis

Write a good Alternative H1 and Null Hypothesis Ho for this experiment below. This is the overarching hypothesis.

H1

H0

Variables

Identify the variables in the spaces below.

IV

Identify the Independent Variable(s). Be concise on what you call the IV (one or two words).

Type of IV

Identify whether the variable is categorical (nominal or ordinal) and identify the categories or if the scale is continuous (ratio or interval scale). If there are more than one IVs, repeat sequence IV, Type of IV.

DV

Identify the Dependent Variable(s). Be concise on what you call the DV (one or two words).

Type of DV

Identify whether the variable is categorical (nominal or ordinal) and identify the categories or if the scale is continuous (ratio or interval scale). If there are more than one DVs, repeat sequence DV, Type of DV.

H1b 

This is the hypothesis comparing Group A and Group B. 

Ho1b

Variables

Identify the variables in the spaces below.

IV

Identify the Independent Variable(s). Be concise on what you call the IV (one or two words).

Type of IV

Identify whether the variable is categorical (nominal or ordinal) and identify the categories or if the scale is continuous (ratio or interval scale). If there are more than one IVs, repeat sequence IV, Type of IV.

DV

Identify the Dependent Variable(s). Be concise on what you call the DV (one or two words).

Type of DV

Identify whether the variable is categorical (nominal or ordinal) and identify the categories or if the scale is continuous (ratio or interval scale). If there are more than one DVs, repeat sequence DV, Type of DV.

Design

Report the design of this experiment including the factors in a table as seen on page 333.

Refer to the list of designs we have learned posted in Week 6’s lab.  Select as many as are applicable and clearly explain why this study fits the designs selected.   

Participants

Describe the participants, their location, and any other descriptions appropriate for a Participant section.

Materials

List and describe the materials and measures used. Address the reliability and validity for each as best as you can, demonstrating a clear understanding of these terms. Use sub headers in APA format.

Note – Please include the citation/reference for psytool kit (the survey experiment):

Stoet, G. (2010). PsyToolkit – A software package for programming psychological experiments using Linux. Behavior Research Methods, 42(4), 1096-1104.

Stoet, G. (2017). PsyToolkit: A novel web-based method for running online questionnaires and reaction-time experiments. Teaching of Psychology, 44(1), 24-31.

Procedure

Describe the procedure for this study in your own words.

Results

Analysis for the results is reviewed in the Week 7 discussion. Make sure to have your datasheet ready to go and follow along with the recording.

In this section, you will report the results of two simple Independent Samples T-tests. These will include reporting the means, standard deviations, and p values. Notice on the data sheet for this week there are two sheets with templates for t-tests. Simply cut and paste the correct data cells into the sheet to be able to compare the means (what a t-test does). Do this first for the overall comparison of Music versus no Music and then to compare the conditions. Make sure to use the difference between the scores (test minus base line) for the comparison of the conditions. This is the response time changed (i.e.. how much it changed from baseline to condition).

Use this template for reporting the results. There should be two T-tests reported. Fill in the Variables as appropriate:

An Independent Sample T-Test revealed that _____________ ( n= xx , M = xxx , SD = xxx) was __________[insert here what the relationship was- significantly greater? Significantly less than? Not significantly different? ] than ________________ ( n = , M = xxxx, SD = XXXX, t(df) = xx.xx, p= .xxx) .

Notes on Reporting : The p = actual value when it is > .05; When it is less than .05 it should be p < .05, p < .01 or p < .001.

M's and SD's are to two decimal places, but p value to 3 decimal places.

N, M, SD, t, p and other stats abbreviations are italicized. Use N for the entire sample and n for part of the sample.

Include two graphs or charts in APA format. Use the examples in your textbook to help. You can create these in excel and paste them here or you can create these in a different way. If you are not familiar with how to create these in excel, here is a link that allows you to create graphs and charts by plugging in numbers: http://www.rapidtables.com/tools/index.htm

Discussion

Discuss what the results mean here. Interpret and explain them so they make sense. Report the internal and external validity and reliability of this experiment here.

This is the story. This is where you must think and provide a story (or clear explanation) about why the results are what they are.

Limitations

Disclose the limitations of the study. Be specific.

Future Work

Suggests some logical next steps in exploring this subject area and why those steps would be important to take next.

2

,

Raw Data Phase 1

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ID Gender DateTaken Music Phase 1- Task A Phase 2 Task B
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Jolene F 4/3/23 2.82 1.66 0.67 2.75 1.33 2.85 2.91 2.82 0.92 1.11 2.16 2.70 1.40 1.03 1.24 1.47 2.43 1.83 0.95 0.87 1.36 0.76 2.47 0.63 1.75 1.34 2.03 2.34 2.64 1.27 1.83 1.91 2.40 1.98 1.70 2.89 2.03 1.44 1.89 2.55 1.00 1.59 1.49 2.76 1.08 4.40 4.15 1.06 2.71 0.66 0.56 1.75 1.75 1.12 0.53 0.55 1.34 1.75 2.11 2.23 1.97 1.16 0.56 2.07 1.48 2.04 0.87 0.47 0.82 2.51 0.61 1.93 1.33 0.51 2.64 1.65 1.98 0.75 1.47 0.47 2.01 2.55 2.10 1.95 1.82 1.22 2.46 1.94 1.29 2.60
Teneisha F 4/4/23 2.50 1.46 1.59 0.92 5.09 2.87 2.90 1.66 2.23 0.67 0.91 1.73 1.76 1.87 0.76 2.73 2.57 1.53 2.98 1.81 0.76 1.04 1.62 0.80 2.59 1.45 1.50 1.68 1.83 1.47 1.10 2.40 0.85 2.01 0.72 2.20 1.15 2.88 1.81 0.71 1.71 0.41 2.05 2.44 2.72 2.59 2.75 1.37 1.20 2.78 0.70 2.70 0.53 1.41 1.53 1.06 2.53 0.67 1.66 0.86 2.19 2.39 0.69 2.59 0.99 1.47 0.44 0.61 2.21 1.35 0.99 2.71 0.55 0.43 0.96 1.42 2.69 2.32 2.01 2.44 2.70 0.71 1.25 2.63 1.31 2.72 1.36 1.72 0.89 0.61
Debora F 4/3/23 2.58 2.70 0.94 0.75 1.09 2.93 1.79 1.94 2.81 1.23 0.97 2.08 0.64 1.02 2.86 2.73 1.50 1.44 1.71 2.52 1.78 2.92 0.67 2.53 0.73 1.17 1.77 1.29 1.75 2.58 2.21 1.81 0.81 2.28 0.96 1.90 1.97 2.13 0.74 1.98 1.47 1.77 2.44 0.66 2.02 1.47 1.87 1.75 2.19 1.79 2.16 1.27 0.49 1.33 0.86 2.42 2.18 2.36 1.10 2.73 2.25 0.60 1.44 1.68 2.08 1.79 1.86 1.77 0.44 1.58 2.18 2.56 2.55 1.82 2.36 1.47 2.25 1.73 1.82 1.31 0.72 2.40 1.72 1.04 1.33 2.21 1.02 2.25 0.58 1.56
Dominique F 4/6/23 0.83 4.65 0.60 0.41 1.66 5.08 1.70 1.66 3.89 3.82 3.21 5.12 4.20 4.31 1.43 5.11 4.86 3.36 4.13 1.72 2.68 2.98 4.85 0.93 2.14 3.01 4.58 1.59 2.14 5.18 1.66 1.88 2.08 1.62 2.77 2.81 2.04 1.24 2.42 2.83 4.44 1.02 1.98 5.07 4.67 1.46 1.02 1.75 4.00 3.70 2.18 3.62 4.51 2.31 1.91 2.25 3.69 2.00 2.75 0.95 2.06 2.28 3.58 3.56 0.90 3.81 4.64 5.18 0.98 1.71 3.58 4.27 2.28 2.46 3.10 1.97 4.91 3.26 1.36 2.18 1.43 3.17 3.48 4.56 4.35 1.48 3.74 2.82 4.76 4.53
Justina F 4/5/23 0.64 2.60 1.08 2.73 1.97 1.48 1.13 1.72 2.23 2.99 0.72 2.95 2.54 1.23 1.92 1.28 0.67 1.34 1.20 0.88 1.00 1.25 1.95 1.88 1.61 2.98 2.69 2.13 2.78 1.29 4.15 0.71 2.62 1.30 1.01 1.29 0.86 0.72 1.51 2.65 1.72 1.10 0.99 1.29 1.01 1.38 1.48 1.39 1.58 1.78 0.46 2.65 1.55 1.23 1.51 0.94 1.15 1.25 0.71 2.74 1.92 1.15 1.68 1.02 2.73 2.43 0.90 2.74 0.49 2.59 1.90 1.17