Is the relationship statistically significant
Stuck with a difficult assignment? No time to get your paper done? Feeling confused? If you’re looking for reliable and timely help for assignments, you’ve come to the right place. We promise 100% original, plagiarism-free papers custom-written for you. Yes, we write every assignment from scratch and it’s solely custom-made for you.
Order a Similar Paper Order a Different Paper
Is the relationship statistically significant
UNDERSTANDING RESEARCH RESULTS: STATISTICAL INFERENCE
© 2012 The McGraw-Hill Companies, Inc.
© 2012 The McGraw-Hill Companies, Inc.
*
© 2012 The McGraw-Hill Companies, Inc .
Explain how researchers use inferential statistics to evaluate sample data
Distinguish between the null hypothesis and the research hypothesis
Discuss probability in statistical inference, including the meaning of statistical significance
© 2012 The McGraw-Hill Companies, Inc.
© 2012 The McGraw-Hill Companies, Inc.
*
Describe the t test, and explain the difference between one-tailed and two-tailed tests
Describe the F test, including systematic variance and error variance
Distinguish between Type I and Type II errors
© 2012 The McGraw-Hill Companies, Inc.
© 2012 The McGraw-Hill Companies, Inc.
*
Discuss the factors that influence the probability of a Type II error
Discuss the reasons a researcher may obtain nonsignificant results
Define power of a statistical test
Describe the criteria for selecting an appropriate statistical test
© 2012 The McGraw-Hill Companies, Inc.
© 2012 The McGraw-Hill Companies, Inc.
*
Inferential statistics are necessary because
the results of a given study are based on data obtained from a single sample of researcher participants and
Data are not based on an entire population of scores
Allows conclusions on the basis of sample data
© 2012 The McGraw-Hill Companies, Inc.
© 2012 The McGraw-Hill Companies, Inc.
*
Allow researchers to make inferences about the true differences in populations of scores based on a sample of data from that population
Allows that the difference between sample means may reflect random error rather than a real difference
© 2012 The McGraw-Hill Companies, Inc.
© 2012 The McGraw-Hill Companies, Inc.
*
Null Hypothesis
H0: The means of the populations from which the samples were drawn equal
Research Hypothesis
H1: The means of the populations from which the samples were drawn equal
© 2012 The McGraw-Hill Companies, Inc.
© 2012 The McGraw-Hill Companies, Inc.
*
Probability: The Case of ESP
Are correct answers due to chance or due to something more?
Sampling Distributions
Sample Size
© 2012 The McGraw-Hill Companies, Inc.
© 2012 The McGraw-Hill Companies, Inc.
*
t value is a ratio of two aspects of the data
The difference between the group means and
The variability within groups
© 2012 The McGraw-Hill Companies, Inc.
t= | group difference |
within-group difference |
© 2012 The McGraw-Hill Companies, Inc.
*
© 2012 The McGraw-Hill Companies, Inc.
© 2012 The McGraw-Hill Companies, Inc.
*
© 2007 The McGraw-Hill Companies, Inc.
Degrees of Freedom
One-Tailed
Two-Tailed Tests
The F Test (analysis of variance)
Systematic variance
Error variance
© 2012 The McGraw-Hill Companies, Inc.
© 2012 The McGraw-Hill Companies, Inc.
*
Calculating Effect Size
Confidence Intervals and Statistical Significance
Statistical Significance
© 2012 The McGraw-Hill Companies, Inc.
© 2012 The McGraw-Hill Companies, Inc.
*
Type I Errors
Made when the null hypothesis is rejected but the null hypothesis is actually true
Obtained when a large value of t or F is obtained by chance alone
© 2012 The McGraw-Hill Companies, Inc.
© 2012 The McGraw-Hill Companies, Inc.
*
Type II Errors
Made when the null hypothesis is accepted although in the population the research hypothesis is true
Factors related to making a Type II error
Significance (alpha) level
Sample size
Effect size
© 2012 The McGraw-Hill Companies, Inc.
© 2012 The McGraw-Hill Companies, Inc.
*
© 2012 The McGraw-Hill Companies, Inc.
© 2012 The McGraw-Hill Companies, Inc.
*
© 2007 The McGraw-Hill Companies, Inc.
Researchers traditionally have used either a .05 or a .01 significance level in the decision to reject the null hypothesis
The significance level chosen is usually dependent on the consequences of making a Type I vs. Type II error.
© 2012 The McGraw-Hill Companies, Inc.
© 2012 The McGraw-Hill Companies, Inc.
*
- Power is a statistical test that determines optimal sample size based on probability of correctly rejecting the null hypothesis
Power = 1 – p (probability of Type II error)
- Effect sizes range and desired power
- Smaller effect sizes require larger samples to be significant
- Higher desired power demands a greater sample size
- Researchers usually strive power between .70 and .90
© 2012 The McGraw-Hill Companies, Inc.
© 2012 The McGraw-Hill Companies, Inc.
*
- Scientists attach little importance to results of a single study
- Detailed understanding requires numerous studies examining same variables
- Researchers look at the results of studies that replicate previous investigations
© 2012 The McGraw-Hill Companies, Inc.
© 2012 The McGraw-Hill Companies, Inc.
*
- Is the relationship statistically significant?
- H0: r = 0 and
- H1: r ≠ 0
- It is proper to conduct a t-test to compare the
r-value with the null correlation of 0.00
© 2012 The McGraw-Hill Companies, Inc.
© 2012 The McGraw-Hill Companies, Inc.
*
Software Programs include
SPSS
SAS
Minitab
Microsoft Excel
Steps in analysis
Input data
Rows represent cases or each participant’s scores
Columns represent for a participant’s score for a specific variable
Conduct analysis
Interpret output
© 2012 The McGraw-Hill Companies, Inc.
© 2012 The McGraw-Hill Companies, Inc.
*
One Independent Variable
Nominal Scale Data
Ordinal Scale Data
Interval or Ratio Scale Data
© 2012 The McGraw-Hill Companies, Inc.
© 2012 The McGraw-Hill Companies, Inc.
*
© 2012 The McGraw-Hill Companies, Inc.
IV | DV | Statistical Test |
Nominal Male-Female | Nominal Vegetarian – Yes / No | Chi Square |
Nominal (2 Groups) Male-Female | Interval / Ratio Grade Point Average | t-test |
Nominal (3 groups) Study time (Low, Medium, High) | Interval / Ratio Test Score | One-way ANOVA |
Interval / Ratio Optimism Score | Interval / Ratio Sick Days Last Year | Pearson’s correlation |
© 2012 The McGraw-Hill Companies, Inc.
*
Multiple Independent Variables
Nominal Scale Data – Factorial Design
Ordinal Scale Data – no appropriate test is available
Interval or Ratio Scale Data – Multiple Regression
© 2012 The McGraw-Hill Companies, Inc.
© 2012 The McGraw-Hill Companies, Inc.
*
*
© 2012 The McGraw-Hill Companies, Inc .
*
*
*
*
*
*
*
*
*
© 2007 The McGraw-Hill Companies, Inc.
*
*
*
*
*
© 2007 The McGraw-Hill Companies, Inc.
*
We’ve proficient writers who can handle both short and long papers, be they academic or non-academic papers, on topics ranging from soup to nuts (both literally and as the saying goes, if you know what we mean). We know how much you care about your grades and academic success. That's why we ensure the highest quality for your assignment. We're ready to help you even in the most critical situation. We're the perfect solution for all your writing needs.
Get a 15% discount on your order using the following coupon code SAVE15
Order a Similar Paper Order a Different Paper