Aronson and Mills (1959) conducted an experiment to see whether people's liking for a group is influenced by the severity of initiation. They reasoned that when people willingly undergo a severe initiation to become members of a group, they are motivated to think that the group membership must be worthwhile. Otherwise, they would experience cognitive dissonance: Why put up with severe initiation for the sake of a group membership that is worthless? In their experiment, participants were randomly assigned to one of three treatment groups: Group 1 (control) had no initiation.
Addition Rule of Probability
It simply refers to the likelihood of an event taking place whenever the occurrence of an event is uncertain. The probability of a single event can be calculated by dividing the number of successful trials of that event by the total number of trials.
Expected Value
When a large number of trials are performed for any random variable ‘X’, the predicted result is most likely the mean of all the outcomes for the random variable and it is known as expected value also known as expectation. The expected value, also known as the expectation, is denoted by: E(X).
Probability Distributions
Understanding probability is necessary to know the probability distributions. In statistics, probability is how the uncertainty of an event is measured. This event can be anything. The most common examples include tossing a coin, rolling a die, or choosing a card. Each of these events has multiple possibilities. Every such possibility is measured with the help of probability. To be more precise, the probability is used for calculating the occurrence of events that may or may not happen. Probability does not give sure results. Unless the probability of any event is 1, the different outcomes may or may not happen in real life, regardless of how less or how more their probability is.
Basic Probability
The simple definition of probability it is a chance of the occurrence of an event. It is defined in numerical form and the probability value is between 0 to 1. The probability value 0 indicates that there is no chance of that event occurring and the probability value 1 indicates that the event will occur. Sum of the probability value must be 1. The probability value is never a negative number. If it happens, then recheck the calculation.
- Aronson and Mills (1959) conducted an experiment to see whether people's liking for a group is influenced by the severity of initiation. They reasoned that when people willingly undergo a severe initiation to become members of a group, they are motivated to think that the group membership must be worthwhile. Otherwise, they would experience cognitive dissonance: Why put up with severe initiation for the sake of a group membership that is worthless? In their experiment, participants were randomly assigned to one of three treatment groups:
Group 1 (control) had no initiation.
Group 2 (mild) had a mildly embarrassing initiation (reading words related to sex out loud).
Group 3 (severe) had a severely embarrassing initiation (reading sexually explicit words and obscene words out loud).
After the initiation, each person listened to a standard tape-recorded discussion among the group that they would now supposedly be invited to join; this was made up made to be as dull and banal as possible. Then, they were asked to rate how interested they thought the discussion was. The researchers expected that people who had undergone the most embarrassing initiation would evaluate the discussion more positively. In the table below, a higher score represents a more positive evaluation.
Experimental Condition
|
|
Control (No Initiation) |
Mild Initiation |
Severe Initiation |
|
Mean |
80.2 |
81.8 |
97.6 |
|
SD |
13.2 |
21.0 |
16.6 |
|
N |
21 |
21 |
21 |
Source: Aronson and Mills (1959).
|
Results of t Tests Between Group Means |
t |
P (Two-Tailed) |
|
Control versus severe |
3.66 |
.001 |
|
Mild versus severe |
2.62 |
.02 |
|
Control versus mild |
.29 |
ns |
a. Were the researchers’ predictions upheld?
b. Calculate an effective size (n2) for each of the three t ratios and interpret these.
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