Background Info Opportunity for people to visually see their brainwave patterns through visual and audio cues on the computer Games and activities are.

Slides:



Advertisements
Similar presentations
Confidence Intervals, Effect Size and Power
Advertisements

Learning Objectives Copyright © 2002 South-Western/Thomson Learning Data Analysis: Bivariate Correlation and Regression CHAPTER sixteen.
Learning Objectives 1 Copyright © 2002 South-Western/Thomson Learning Data Analysis: Bivariate Correlation and Regression CHAPTER sixteen.
July, 2000Guang Jin Statistics in Applied Science and Technology Chapter 9_part I ( and 9.7) Tests of Significance.
PSY 307 – Statistics for the Behavioral Sciences
Fundamentals of Hypothesis Testing. Identify the Population Assume the population mean TV sets is 3. (Null Hypothesis) REJECT Compute the Sample Mean.
Chapter Goals After completing this chapter, you should be able to:
Correlations and T-tests
8-4 Testing a Claim About a Mean
Aaker, Kumar, Day Seventh Edition Instructor’s Presentation Slides
UNDERSTANDING RESEARCH RESULTS: STATISTICAL INFERENCE © 2012 The McGraw-Hill Companies, Inc.
Today Concepts underlying inferential statistics
Summary of Quantitative Analysis Neuman and Robson Ch. 11
Hypothesis Testing Using The One-Sample t-Test
Richard M. Jacobs, OSA, Ph.D.
1 Nominal Data Greg C Elvers. 2 Parametric Statistics The inferential statistics that we have discussed, such as t and ANOVA, are parametric statistics.
Statistical Analysis. Purpose of Statistical Analysis Determines whether the results found in an experiment are meaningful. Answers the question: –Does.
Inferential Statistics
Example of Simple and Multiple Regression
Week 12 Chapter 13 – Association between variables measured at the ordinal level & Chapter 14: Association Between Variables Measured at the Interval-Ratio.
Statistics for the Social Sciences Psychology 340 Fall 2013 Thursday, November 21 Review for Exam #4.
AM Recitation 2/10/11.
Statistical Analysis I have all this data. Now what does it mean?
Aaker, Kumar, Day Ninth Edition Instructor’s Presentation Slides
Chapter 13: Inference in Regression
Correlation and Linear Regression
Overview of Statistical Hypothesis Testing: The z-Test
Comparing Means From Two Sets of Data
1 Tests with two+ groups We have examined tests of means for a single group, and for a difference if we have a matched sample (as in husbands and wives)
Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Chapter 17 Inferential Statistics.
Copyright © 2008 Wolters Kluwer Health | Lippincott Williams & Wilkins Chapter 22 Using Inferential Statistics to Test Hypotheses.
Statistics Definition Methods of organizing and analyzing quantitative data Types Descriptive statistics –Central tendency, variability, etc. Inferential.
Chapter 9 Part C. III. One-Tailed Tests B. P-values Using p-values is another approach to conducting a hypothesis test, yielding the same result. In general:
Chapter 15 Data Analysis: Testing for Significant Differences.
Hypothesis Testing CSCE 587.
Statistical Analysis I have all this data. Now what does it mean?
QMS 6351 Statistics and Research Methods Regression Analysis: Testing for Significance Chapter 14 ( ) Chapter 15 (15.5) Prof. Vera Adamchik.
T-TEST Statistics The t test is used to compare to groups to answer the differential research questions. Its values determines the difference by comparing.
1 1 Slide Simple Linear Regression Coefficient of Determination Chapter 14 BA 303 – Spring 2011.
© 2011 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license.
A Course In Business Statistics 4th © 2006 Prentice-Hall, Inc. Chap 9-1 A Course In Business Statistics 4 th Edition Chapter 9 Estimation and Hypothesis.
1 Chapter 12 Simple Linear Regression. 2 Chapter Outline  Simple Linear Regression Model  Least Squares Method  Coefficient of Determination  Model.
Chapter 10: Analyzing Experimental Data Inferential statistics are used to determine whether the independent variable had an effect on the dependent variance.
Chapter 12 A Primer for Inferential Statistics What Does Statistically Significant Mean? It’s the probability that an observed difference or association.
Testing Hypothesis That Data Fit a Given Probability Distribution Problem: We have a sample of size n. Determine if the data fits a probability distribution.
Chapter 9 Three Tests of Significance Winston Jackson and Norine Verberg Methods: Doing Social Research, 4e.
Statistics for Business and Economics 8 th Edition Chapter 11 Simple Regression Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Ch.
Chapter 13 - ANOVA. ANOVA Be able to explain in general terms and using an example what a one-way ANOVA is (370). Know the purpose of the one-way ANOVA.
1 ANALYSIS OF VARIANCE (ANOVA) Heibatollah Baghi, and Mastee Badii.
Chapter Seventeen. Figure 17.1 Relationship of Hypothesis Testing Related to Differences to the Previous Chapter and the Marketing Research Process Focus.
METHODS IN BEHAVIORAL RESEARCH NINTH EDITION PAUL C. COZBY Copyright © 2007 The McGraw-Hill Companies, Inc.
Chapter Thirteen Copyright © 2006 John Wiley & Sons, Inc. Bivariate Correlation and Regression.
Three Broad Purposes of Quantitative Research 1. Description 2. Theory Testing 3. Theory Generation.
Chapter Eight: Using Statistics to Answer Questions.
Chapter 6: Analyzing and Interpreting Quantitative Data
© Copyright McGraw-Hill 2004
Formulating the Hypothesis null hypothesis 4 The null hypothesis is a statement about the population value that will be tested. null hypothesis 4 The null.
Regression Analysis. 1. To comprehend the nature of correlation analysis. 2. To understand bivariate regression analysis. 3. To become aware of the coefficient.
Copyright c 2001 The McGraw-Hill Companies, Inc.1 Chapter 11 Testing for Differences Differences betweens groups or categories of the independent variable.
Research Methods and Data Analysis in Psychology Spring 2015 Kyle Stephenson.
Chapter 13 Understanding research results: statistical inference.
Educational Research Inferential Statistics Chapter th Chapter 12- 8th Gay and Airasian.
Hypothesis Testing. Steps for Hypothesis Testing Fig Draw Marketing Research Conclusion Formulate H 0 and H 1 Select Appropriate Test Choose Level.
1 1 Slide IS 310 – Business Statistics IS 310 Business Statistics CSU Long Beach.
Correlation and Linear Regression
Factorial Experiments
Inference and Tests of Hypotheses
UNDERSTANDING RESEARCH RESULTS: STATISTICAL INFERENCE
Chapter Nine: Using Statistics to Answer Questions
COMPARING VARIABLES OF ORDINAL OR DICHOTOMOUS SCALES: SPEARMAN RANK- ORDER, POINT-BISERIAL, AND BISERIAL CORRELATIONS.
Presentation transcript:

Background Info Opportunity for people to visually see their brainwave patterns through visual and audio cues on the computer Games and activities are included in neurofeedback software such as BrainTrain that provides reinforcements whenever goals are met Goals are associated with the appropriate proportions between beta and theta brain waves which relate to neurological patterns found in people with such symptoms as ADHD, ADD, TBI, PTSD, Anxiety and other types of disorders

Purpose  To learn how to use the neurofeedback equipment efficiently  To determine the best practices regarding the delivery of neurofeedback  To explore the use of neurofeedback through specific cases

Research Question  How does Neurofeedback affect a student diagnosed with ADHD, overall ability to decrease cognitive and behavioral symptoms associated with ADHD (focus, decreased hyperactivity, impulsivity, distractibility and improved memory)?  How does Neurofeedback affect a student’s overall self-awareness and self- esteem?  Does Neurofeedback improve the ‘overall quality of life for the student?

Variables  Independent Variable(s) [IV] : Neurofeedback  Dependent Variable [DV]: increase memory, less, hyperactivity, impulsivity and distractibility, improvement in overall quality of life.

Hypothesis  Hypothesis 1: Individuals who receive Neurofeedback treatment will see an increase in their ability to focus, and increase in memory, and they will experience less hyperactivity, impulsivity, and distractibility.  Null Hypothesis 1: Individuals who receive Neurofeedback treatment will not see an increase in their ability to focus, and increase in memory, and they will experience less hyperactivity, impulsivity, and distractibility.  Hypothesis 2: Neurofeedback leads to an improved ‘overall quality of life’ for the student, self-awareness, and self-esteem.  Null Hypothesis 2: Neurofeedback does not nor has no effect on the ‘overall quality of life’ for the student, self- awareness, and self-esteem.

Likert Scale Responses 1. strongly agree 2. agree 3. neutral 4. disagree 5. strongly disagree

Descriptive Statistics

T-Test

 All questions in the sample rejected the null hypothesis due to the fact that the calculated t for each question surpasses the one-tailed critical t and its individual upper Confidence Interval; therefore, each question proves that Neurofeedback has an impact on an individual’s ability to focus, and increase memory, and they will experience less hyperactivity, impulsivity, and distractibility which has the possibility of improving their overall quality of life. Group Statistics genderNMeanStd. DeviationStd. Error Mean q1Male Female q2Male Female q3Male Female

One Sample This output tells us that we have 51 observations (N), the mean number ranges between is and the standard deviation of the sample is The standard error of the mean (the standard deviation of the sampling distribution of means) ranges between

 When looking at the data with a 95% confidence interval of the difference. The degree of freedom is 50 due to 51-1 (N-1). The fourth column tells us the two-tailed significance (the 2-tailed p value.) Because this is a two-tailed test, look in a table of critical t values to determine the critical t. The critical t with 50 degrees of freedom, α =.05 and two-tailed is  Determine if we can reject the null hypothesis or not. The decision rule is: if the two- tailed critical t value is less than the observed t AND the means are in the right order, then we can reject H0. In this example, the critical t is (from the table of critical t values) and the observed t is , so we reject H0. That is, there is insufficient evidence to conclude that the null hypothesis is rejected.

ANOVA

Scheffe

 All F values are between.266 to Due to the fact that all F values listed above are less than the Critical F value we cannot reject the null the hypothesis. In order to reject the null hypothesis the F value has to meet or be greater than the Critical F value  The Scheffe Post Hoc Test reflect that fact that, Q3 demonstrated the highest significance at.752 while Q2 had the lowest significance at.600. Ultimately, since the ANOVA did not reject the null hypothesis, the Scheffe test was not necessary.

Regression The line of regression shows a positive correlation between Neurofeedback (x axis) and increase in their ability to focus, and increase in memory, and they will experience less hyperactivity, impulsivity, and distractibility (y axis). This does not necessarily mean they are connected to one another, only that there is a correlation. The equation is 0.75 * x R squared showed that this variation only has a 0.028% likelihood of directly impacting the other variable meaning that there is less than a 99% impact coming from a different variable

Chi-Square Crosstabulation assessment we found a correlation, but with the CHi-square test it was not as significant

The graph reflects a major attitude difference between male and female participants. The graph also reflects that fact that a large number of male students responded compared to the number of female students. Male students were more like to strongly agree with the treatment of Neurofeedback and female students were less likely. Sophomore students reflect the large number of participants in this student and also reflect the number of students that strongly agree that the treatment was very effective.

Hypothesis Test Summary Hypothesis Test Summary was conducted and found that there was evidence of significance of 0.5 and it retain the null hypothesis.

Best Approach In this study the best supporting approach would be the t-test. The t-test determines the relationship between the independent and dependent variables. The hypothesis summary indicated a rejection of the null hypothesis.