Welcome Back - PowerPoint PPT Presentation

1 / 17
About This Presentation
Title:

Welcome Back

Description:

... they are simply measured As such cannot infer causality Can t say X causes Y ... strong relationship is present Doesn t mean ice cream causes crime ... – PowerPoint PPT presentation

Number of Views:51
Avg rating:3.0/5.0
Slides: 18
Provided by: bakers2
Category:
Tags: back | causes | crime | welcome

less

Transcript and Presenter's Notes

Title: Welcome Back


1
Welcome Back
  • Learning Objectives
  • Identify variables in research
  • Describe Relationships btwn
  • Explain why samples used to describe population
  • Explain random sampling and representative
    samples
  • Distinguish btwn Descriptive Inferential Stats
  • Distinguish btwn experimental correlational
    study
  • Identify distinguish scales of measurement

2
Research Process
  • Interest in something
  • Playing video games leads to violence
  • Goal Discover LAWS OF NATURE
  • Somethings are called Variables
  • Variables
  • Independent variables- the thing that
    influences the behavior
  • Dependent variables- the outcome or result of the
    independent variable

3
Examples of Variables
  • Independent
  • Vegetables
  • Vitamins
  • Drugs
  • Smiling
  • Examples?
  • Dependent
  • Cancer
  • Immune System
  • Alzheimers
  • Helping or Altruism
  • Examples?

4
Relationship between Variables
  • Relationship occurs when a chg in one var. is
    accompanied by a consistent chg. in another var.
  • Strength Degree of chg in X is associated with
    chg in Y
  • Types of relationships
  • Increase, increase
  • Increase, decrease
  • Decrease, decrease
  • Zero

5
Populations Samples
  • Population-all members of group
  • Parameters-numbers that describe
  • Sample-subset of pop designed to be
    representative
  • Statistic-numbers that describe

Every student at BC
Students in a History class at BC
6
  • http//www.ruf.rice.edu/lane/stat_sim/sampling_di
    st/
  • Why?
  • Cheaper
  • Practical
  • Representative

7
What is done to samples?
  • Describe
  • Use descriptive statistics to organize
    summarize characteristics of data
  • Example The average test score was 87
  • Infer
  • Use inferential statistics to decide whether
    sample data represents a particular relationship
    in population
  • Example Reading the textbook significantly
    increased test scores.

8
Characteristics of a Study
  • Question about characteristic of sample or pop is
    asked
  • Design study to answer question
  • Who -How many -When -What
  • Conduct study
  • Correlational
  • Experimental

9
Correlational Study
  • Goal To determine if relationship btwn two or
    more var is present
  • No variables are manipulated or made to occur,
    they are simply measured
  • As such? cannot infer causality
  • Cant say X causes Y
  • Only X and Y are related

10
Example
  • Researchers Question
  • -Is there a relationship btwn ice cream sales
    and crime rate?
  • Design of study measure sales crime rates
  • Yes, a positive, strong relationship is present
  • Doesnt mean ice cream causes crime

11
Experimental Study
  • Goal To determine if relationship (causality)
    exists btwn variables
  • Variable (indep) are manipulated or changed to
    see chg in beh (dep var)
  • Can infer causality
  • X causes chg in Y
  • Caution causal statement based on probability
  • Never says PROVES
  • Other variables could be responsible for change
    in dependent variable

12
Example
  • Researchers Question
  • -Does ice cream cause or have an effect on
    criminal behavior
  • Design of study Ps in diff conditions of ice
    cream (levels of indep var) and measure criminal
    beh (dep var)
  • Yes, a probable causal relationship is present
  • Ps that ate 1 or 2 scoops of ice cream committed
    more crimes
  • PROBABILITY

13
Type of Data or Characteristics of Scores
  • Type of data or dependent var youre interested
    in will determine what statistic you can use
  • Numbers you record have diff mathematical
    characteristics
  • Characteristics of numbers
  • Levels of measurement
  • Continuous or discrete

14
Scales of Measurement
  • Nominal Scale scores used for identification or
    naming. Ex categories
  • Ordinal Scale scores indicate rank or ordering.
    Ex relative amount
  • Interval Scale scores indicate actual amount.
    Ex numbers
  • 0 doesnt necessarily mean non
  • Ratio Scale scores indicate actual amount Ex
    numbers (0 actually means none)

15
Continuous or Discrete
  • Continuous allows fractional amounts (continues
    btwn whole numbers)
  • Usually Scale (ratio interval)
  • Test score 97.6
  • IQ score 145.9
  • Discrete measures only whole numbers
  • Usually Nominal or Ordinal
  • Male or Female
  • Eye color
  • Can be Scale
  • Ice cream or no ice cream
  • No. of crimes 3

16
Lets Graph
17
Questions?
  • Lets get Active with a CLE
  • Homework Finish Ch.1 2 study guid
  • Review notes text
  • Finish Ch. 1 2 of study guide
  • Preview Ch. 3
  • Bring
  • Questions, book, calculator, pencils
  • Be ready for quiz
Write a Comment
User Comments (0)
About PowerShow.com