Module #3: Research Strategies

Research Strategies  We will look at 3 different types of research methods: 1. Descriptive a. case studies b. surveys c. naturalistic observations 2. Correlational 3. Experimental

Descriptive – Case Study  Case Study – studying one individual in detail, thinking it will lead to information about all people.  Jean Piaget (Cognitive Stages of Development) studied children to discover information about learning.  Case studies sometimes were misleading because there are always exceptions.  The one being studied might be unusual and does not tell us about human behavior.

Descriptive – Case Study  Famous Case Study: Genie (feral child).  Genie was the victim of severe abuse.  She was locked alone in a room for the first 13 years of her life strapped to a toilet or bound to a crib with her arms and legs tied.  She was never spoken to and thus never acquired a language.  Upon rescue she gradually started to acquire language skills.

Descriptive – Case Study  She lived at the institution where she was being studied for 4 years.  After leaving institution she bounced around different places where she experienced more abuse and her language skills began to regress.  In 2008 it was reported that Genie was living in California in psychological confinement, speechless.

Descriptive – Surveys  Surveys – Ask people to report on their behavior/opinions.  Less depth than case studies but are asking larger number of people.  Wording can have a major effect in surveys and can have a big affect in answers given.  “Do you believe in helping the needy?” Vs.  “Do you support welfare programs?”

Descriptive – Surveys  False consensus effect – We surround ourselves with people that have similar habits and attitudes. This leads us to assume everyone thinks and acts like we do.  Representative sample is to randomly survey people from all backgrounds and experiences.  Population – everyone you want to study and describe.  Random sample – a sample that fairly represents the population.

Descriptive – Surveys  Example: Conducting a survey on the theme for Senior Prom.  Population: Senior Class  Random Sample: The seniors in this class DO NOT represent a random sample.  You would need representatives from all the various levels of classes. (Reg, Hon, etc.)  Large samples are better than small ones, but must be representative.

Descriptive – Surveys  Accuracy of data is an issue because people sometimes distort their answers or fail to recall information correctly.  In the 1970s, researchers noticed a lot of babies were born with deformed limbs.  They found the strongest relationship between the mothers was the drug thalidomide during pregnancies.  Controlled experiments with rats verified the drug caused abnormal limb development in babies.

Descriptive – Observations  Naturalistic Observations – watching and recording behavior in their natural environment.  Does not explain behavior, it describes it.  Jane Goodall – #1 expert on chimpanzees. Conducted a 45 year study of wild chimps in Tanzania, Africa.

Correlation  Correlation – When two things have a relationship and are dependent of each other. It allows one to predict the other.  Correlation Coefficient – How much two things are correlated. From -1 to +1. r = Direction of relationship: positive or negative. Strength of correlation. Higher number means a stronger correlation.

Correlation  Positive Correlation – Two things rise and fall together. In this example, the more years of education you have, the older you are when you have your first child.

Correlation  Negative Correlation – Inverse relationship. When one rises, the other falls.  Weak correlation has a coefficient near 0. In this example, the more hours of video games played, the lower the GPA.

Correlation How are the following correlated? 1.The more time you study, the higher your test scores. 2.The less you spend, the more you save. 3.The more you work, the more you earn. 4.People who consume more Vitamin D often have fewer colds. 5.An increase in foxes led to a decrease in rabbits. Negative Positive Negative Positive

Correlation  Correlation DOES NOT mean causation.  Because two things are correlated, does not mean they are caused by each other.  Among men, length of marriage is positively correlated with hair loss.  This does not mean that marriage causes hair loss.  Correlation shows a POSSIBLE cause- effect relationship, but does not prove it.

Correlation  Illusory Correlation – When we think two things are correlated, we look for things that confirm our belief even if they aren’t really correlated.  “Being wet and cold does not cause a person to catch a cold.”  It only seems to have a correlation.  We notice random coincidences and assume there is a correlation, even when there is no correlation.

Experimentation  Experiments allow researchers to control conditions to isolate cause and effect.  Experiments manipulate one or more variables, while holding constant other factors, to observe the effect it has on another variable.  An experiment manipulates a factor to determine its effect.

Experimentation  Placebo – a drug that has no medical value given to deceive a participant into thinking they are receiving an actual treatment. Used for control groups.  Double-blind procedure – when both the participant and the research staff are unaware of who received a placebo.  Placebo Effect – improvement of medical condition when given a placebo.  Believing you are getting a treatment can reduce symptoms.

Experimentation  Experimental Condition – A group of people who receive an actual treatment.  Control Condition – A group of people who do not receive the treatment.  Allows comparison of two groups as to the effect of the treatment.  Participants must be assigned randomly (distributed equally amongst experimental and control groups by chance).

Experimentation  Independent Variable (IV) – The experimental factor that is being manipulated. The variable whose effect is being studied.  Dependent Variable (DV) – the variable that may change depending on the independent variable. Outcome of changing the IV.  Experiments manipulate the IV, measure the DV, and control all other variables.  Experiments test the effects of IV.

Experimentation “Experiment on how much a plant grows based on how much water it receives.” Independent Variable – Amount of water plants received. Dependent Variable – The growth of the plants. The growth of the plants depends on how much water the plants received.

Statistical Reasoning  Measures of central tendency – mean, median, and mode.  Mean – Average (sum of scores divided by number of scores)  Median – Midpoint (Order scores and find the middle)  Mode – Most frequent (Score that appears the most)  Range – The difference between the lowest and highest scores.

Statistical Reasoning  Skew – When unusually high or low scores distort the mean. No SkewSkewed!

Statistical Reasoning  Standard Deviation – How much scores deviate from the mean. ScoreDeviation Squared from Mean Deviation Sum of dev = /4 = 79 (mean) Sum of dev. # of scores

Statistical Reasoning Standard Deviation = Standard Deviation = 8.69 = Sum of dev. # of scores √ √

Statistical Reasoning  Statistical Significance – a statistical statement of how likely it is that a result occurred by chance.  If sample averages are reliable and the difference between them is relatively large, then it has statistical significance.