Good day, I am seeking assistance with a project. The class is Psychology 219 Adulthood and Aging.

Remaining sections of project 

 Important Dates and Deadlines

1.         Data analysis

By 4/30,  view and analyze the data (file in blackboard) using Google Sheets.Further down this document are the instructions on how to assess the data, which will include calculating means and Pearson’s correlation coefficients

2.       Report

 By 5/14, you will submit a 1 page research report that will describe and explain your research methods and results finding. I will provide a rubric to assist you in writing the report.

Data analysis                                Data worksheet

I have posted an excel spreadsheet with your data in the project folder on blackboard.

Save the file to your computer, and open with Google Sheets

 https://www.google.com/sheets Open the link and click on Blank. Click File- open. Open the file (upload)

 There are 7 variables that I have left in (for the sake of simplicity). These variables are (in column order):

A: Age

B: Happiness

C: Anxiety about death

D: Regrets

E: Attitude toward aging

F: Number of children

G: Loneliness.

 For the project, you’ll calculate a correlation (measure of the strength of a relationship) between two of these variables (if there is another variable you really want to look at instead, that I did not include in this final file, let me know)

 For example, you could look for a relationship between age and happiness- do we get happier with age? Or Anxiety about death and regrets- are people with more regrets more anxious about dying?

 On page 4 is a worksheet for you to fill out. I’ve given instructions step by step for you to conduct the data analysis (next page). I’ve also given examples for each answer (on the page after the data analysis worksheet). You can find videos showing how to do these types of analysis at these links:

Calculate a mean in Google Sheets:

https://www.youtube.com/watch?v=6F7SItd2Yb0

 To calculate a mean:

1.       Click on a blank cell and enter (without the quotation marks) - "=AVERAGE("

2.       Click on the top cell of the data you want to include, and then hold the mouse button and drag to the bottom of the data you want to include (example, all of the data listed below the header “age”)

3.       Type “)”  and click enter

4.       Or-in the blank cell, type "=AVERAGE(b1:b25)” (without the quotation marks), adjusting the letter and numbers in quotations so that they are the first and last cells of data in the column

5.       Press "Enter" to complete the formula and the mean of your numbers will appear in the cell. Do this for both the age variable data and your other variable data

Calculate a correlation in Google Sheets:

 https://www.youtube.com/watch?v=omIT5V7naqM

 To calculate the correlation coefficient :

1.       Click on a blank cell and enter (without the quotation marks) - "=CORREL("

2.       Click on the top cell of the first variable data you want to include, and then hold the mouse button and drag to the bottom of the data you want to include (example, all of the data listed below the header “age”)

3.       Type “,”

4.       Click on the top cell of the second variable data you want to include, and then hold the mouse button and drag to the bottom of the data you want to include (example, all of the data listed below the header “_____”)

5.       Type “)”  and click enter

6.       Or-in the blank cell, type "=CORREL(b2:b242, c2:c242)” (without the quotation marks), adjusting the letter and numbers in quotations so that they are the first and last cells of data in the columns

Data analysis worksheet                                                                                Name:

1. What two variables will you be analyzing?  

              Variable 1:

Variable 2:

1. What is the mean of variable 1? (this is the average of that variable- all of the data points added up, then divided by the number of data points)

1. What is the mean of variable 2? (this is the average of that variable- all of the data points added up, then divided by the number of data points)

1. What is the correlation coefficient for the relationship between these two variables?

1. Is this a positive or negative correlation? Is it strong, moderate, or weak? Explain the correlation in words. (Page 5 has information on how to interpret a correlation coefficient)

 An example of how to write answers to the data worksheet (NOTE- I’m using fake numbers here! These are not the actual means and correlation of the variables age and happiness!)

Data analysis worksheet                                                              Name: Rebecca West

1. What two variables will you be analyzing?  

               Variable 1: Age

Variable 2: Happiness

1. What is the mean of variable 1?

 Age has a mean of 34.5 This means that the average age of the people who answered the survey was 34.5.

1. What is the mean of variable 2?

 Happiness has mean of 3.8. That means that the people who answered the survey were moderately happy, as the happiness scale is from 1 (not happy at all) to 5 (very happy)

1. What is the correlation coefficient for the relationship between these two variables?

 The correlation coefficient for age and happiness is r= .18

1. Is this a positive or negative correlation? Is it strong, moderate, or weak? Explain the correlation in words.

This is a weak, positive relationship. That means that as people get older, they get happier, but it’s a weak (small) increase in happiness.

Supplementary materials: The concept of covariance  - information to help you understand correlations

Correlation means association - it is a measure of the extent to which two variables are related.  Often, a correlation is linear. That means that the two variables either move (vary) generally in a line- either in the same direction, or in opposite directions.

 A positive correlation is a relationship between two variables in which both variables either increase or decease at the same time. An example would be height (X) and weight (Y). Taller people tend to be heavier.

Is it true that as X increases …Y also increases, and to what extent?

 A negative correlation is a relationship between two variables in which an increase in one variable is associated with a decrease in the other. An example would be height above sea level and temperature. As you climb the mountain (increase in height [X]) it gets colder (decrease in temperature [Y]).

 Is it true that as X increases …Y decreases, and to what extent?

 A zero correlation exists when there is no relationship between two variables. For example there is no relationship between the amount of tea drunk and level of intelligence.

The mere fact that two variables covary (i.e. correlate) is no proof that one is the cause of the other. Correlation does not necessarily prove causation.

A Correlation Coefficient A correlation coefficient is an index number that measures …

The magnitude (strength)

 The closer to 1 or -1 (the further from 0), the stronger the correlation (a general guide below):

  Between 0 and .1, or 0 and -.1, no relationship

 Between .1 and .3, or between -.1 and -.3, weak relationship

 Between .3 and .7, or between-.3 and -.7, moderate relationship

 Between .7 and 1.0, or between -.7 and -1.0, strong relationship

   The direction of the relationship between two variables

 Positive- as variable X increases,  variable Y increases

Negative- as variable X increases, variable Y decreases

 It is designed to range in value between -1.0 and 1.0

Interpreting a correlation

 If a correlation between two variables (example- age and the number of days spent with family) is r=.63

 Then this is a moderate, positive relationship.  As age increases, people spend more days with their family members.

 Report

I am making this a shorter assignment than previously planned. Details are below, and the next two pages give the grading rubric and an example report.

  The report should include the following:

1.       Introduction

a.       Background (use details from the textbook). Describe your variables, and give a detail from the textbook about each of these variables.

b.       Hypothesis

2.       Discussion of your survey:

a.       Method:

                                      i.      Participants (who, how many)

ii.  Variables, defined

  iii.      Procedure (how was the data collected)

b.       Results

 i.      Results of your study- discuss the two variables, how they are correlated (strength, direction, describe in words, also show r value) and their means

c.       Discussion

i.      Did the results match your hypothesis? Why/why not do you think that is the case?

  ii.      What did you learn about the experience of conducting a study about psychological topic? 

Rubric for grading:  

Example report (use as a guideline, the bolded sections are areas that require more information!

Happiness and age

Happiness is one way in which we measure subjective well-being; a way to evaluate the positive feelings in one’s life (Cavanaugh & Blanchard-Fields, 2016). Subjective well being and happiness may change with age. A stereotype of aging is that we grow less happy, more grumpy, but in fact, many studies have suggested that happiness increases with age. My group (The Happy Vampires) were interested in determining if we could replicate this finding; that happiness is associated with increasing age. We hypothesized that  (your hypothesis, and theoretical reason why, with citation from the text book if possible- a few sentences. ) We used chronological age as our measure of age (rather than perceived, psychological, or other measures of age, [Cavanaugh & Blanchard-Fields, 2016]).

Methods: We collected the answer to the following questions; 1) how old are you, and 2) on a scale of 1 to 5 (5 being the happiest), “how happy are you?” 242 people were interviewed (here, detail how you collected your data [using Google forms], who you approached, how, etc).

Results:  (here, discuss the two variables, how they are correlated (strength, direction, describe in words, also show r value and give average of your other variable, for example, age and happiness were correlated at r=.18, a positive weak correlation).  The participants had an average age of 34.5, and an average (mean) happiness level of 3.8 out of 5 (remember to actually calculate this- this is a fake number). The results show that …. the level of happiness is (describe correlation- for example, the level of happiness increases weakly as age increases)…   This confirms/ does not confirm our hypothesis that (name your hypothesis) .

Discussion: According to Cavanaugh (2016), happiness is associated with increasing age, due to(…). We found a similar results; in our study, happiness was correlated with age (…). Though we did not ask additional questions to learn more about this relationship, we believe this result is due to (Here explain why you think you found what you found)

During the course of this project, I learned (describe what you learned about conducting a psychological study, what this kind of study does/does not answer [limitations of the short survey, etc.], what other work/studies could be done so that we could better understand the relationship between your variables, etc.).

References

Cavanaugh, J. C., & Blanchard-Fields, F. (2016). Adult development and aging. Cengage Learning.