Createa 12- to 15-slide presentation using the information you gathered and submitted in Weeks 3 and 4. Include the following:
·Describe the problem and provide some brief background information about the situation.
·Explain the research hypothesis.
·Describe your sample and your sampling method.
·Explain the four steps of the research process you followed, and define the critical value and the test statistic your analysis provided.
·Provide the main finding of the study. What did you prove or fail to prove?
·Provide recommendations based on your findings.
Formatany citations in your presentation according to APA guidelines.
will send in book and both papers for referencing and use must use book as well
Title page for power point Inferential Research and Statistics Project Part 3 (General Psychology) By:Tamiya Anderson PSY/315 Professor: Celine Cate Create a 12- to 15-slide presentation using the information you gathered and submitted in Weeks 3 and 4. Include the following: Describe the problem and provide some brief background information about the situation. Explain the research hypothesis. Describe your sample and your sampling method. Explain the four steps of the research process you followed, and define the critical value and the test statistic your analysis provided. Provide the main finding of the study. What did you prove or fail to prove? Provide recommendations based on your findings. Format any citations in your presentation according to APA guidelines. Expectations for PowerPoint Presentations Ensure you develop your presentations with the proper number of slides suggested under the assignment and meet the learning objectives for the presentation as well. You are required to include at least 3 credible research sources, one of which MUST be the textbook, for presentations. Sources and graphics need to be properly cited and referenced in APA 7th edition style. You need to include in-text citations on each of your individual slides in addition to completing reference slides at the end of the presentation. Keep in mind your title slide should include your presentation title, your name, and the date of submission. Slides should have no more than 7 words a line and 7 lines per slide (7x7 rule), using short phrases and simple sentences. Provide only key points on your slides – use your speaker notes for more detailed information. Limit the information on your slides to essentials. Font size on your slides should be between 24-48 points in easy-to-read fonts like Arial, Courier or Times New Roman. If you need multiple slides for your references, this is fine but realize these do not count toward your total slide count for your content. Avoid using ALL CAPS and use the same font style for your entire presentation. Avoid using font colors that are difficult to read – avoid the color red in particular. For a professional look on your slides, use two spaces between all words. Remember to avoid using abbreviations and acronyms on your slides. Graphics and special effects are wonderful but keep in mind not to overload your slides with too many graphics, too much text, or too many effects. The general rule is no more than 2 graphics per slide. However, you should not have a presentation that lacks graphics completely. Also, please ensure you cite/reference your images appropriately in APA style. Ensure you include your Part II Excel output for your t-test on one slide and also explain the corresponding results of this test in the presenter notes. Speaker/presenter notes are required for every slide in the presentation. Presenter notes are where you include your specific information that explains the information on your slides. Your presenter notes should be written using complete sentences (no outlines). Your notes should be where you explain your slides and provide your audience with more information about your topic. Think of your notes as what you would be saying if you were to give this presentation in person to a room full of people. As such, the information should flow and should be clear and free of errors. Your presenter notes and your slides should be proofread and spell-checked. Please ensure your work is original. I do check for plagiarism. 0205414338.pdf Major Formulas Formula Number The mean is the sum of the scores divided by the number of scores. M = gX N (2-1) The variance is the sum of the squared deviations of the scores from the mean, divided by the number of scores. SD 2 = g1X - M22 N (2-2) A Z score is the raw score minus the mean, divided by the standard deviation. Z = X - M SD (3-1) The variance of a distribution of means is the variance of the population of individuals divided by the number of individuals in each sample. �2M = �2 N (5-2) The effect size for the difference between two means is the difference between the population means divided by the population’s standard deviation. d = �1 - �2 � (6-1) The estimated population variance is the sum of the squared deviation scores divided by the number of scores minus 1. S 2 = g1X - M22 N - 1 = SS N - 1 (7-1) The variance of the distribution of means based on an estimated population variance is the estimated population variance divided by the number of scores in the sample. S2M = S2 N (7-5) The t score in a single sample t test, and a t test for dependent means (where you are using difference scores) is your sample’s mean minus the null hypothesis population mean, divided by the standard deviation of the distribution of means. t = M - � SM (7-7) The pooled estimate of the population variance is the degrees of freedom in the first sample divided by the total degrees of freedom (from both samples) multiplied by the population variance estimate based on the first sample, plus the degrees of freedom in the second sample divided by the total degrees of freedom multiplied by the population variance estimate based on the second sample. S2Pooled = df1 dfTotal 1S212 + df2dfTotal1S 2 22 (8-1) The variance of the distribution of means for the first population (based on an estimated population variance) is the pooled estimate of the population variance divided by the number of participants in the sample from the first population. S2M1 = S2Pooled N1 (8-2) The variance of the distribution of differences between means is the variance of the distribution of means for the first population (based on an estimated population variance) plus the variance of the distribution of means for the second population (based on an estimated population variance). S2Difference = S2M1 + S 2 M2 (8-4) The t score in a t test for independent means is the difference between the two sample means divided by the standard deviation of the distribution of differences between means. t = M1 - M2 SDifference (8-7) The within-groups population variance estimate (or mean squares within) is the sum of the population variance estimates based on each sample, divided by the number of groups. S2Within or MSWithin = S21 + S22 + g + S2Last NGroups (9-1) (9-2) S2M = g1M - GM22 dfBetween The estimated variance of the distribution of means is the sum of each sample mean’s squared deviation from the grand mean, divided by the degrees of freedom for the between-groups population variance estimate. (9-4) S2Between or MSBetween = 1S2M21n2 The between-groups population variance estimate (or mean squares between) is the estimated variance of the distribution of means multiplied by the number of scores in each group. (9-5) F = S2Between S2Within or MSBetween MSWithin The F ratio is the between-groups population variance estimate (or mean squares between) divided by the within- groups population variance estimate (or mean squares within). (9-10) S2Between = g1M - GM22 dfBetween or MSBetween = SSBetween dfBetween The between-groups population variance estimate is the sum of squared deviations of each score’s group’s mean from the grand mean divided by the degrees of freedom for the between-groups population variance estimate. (9-11) S2Within = g1X - M22 dfWithin or MSWithin = SSWithin dfWithin The within-groups population variance estimate is the sum of squared deviations of each score from its group’s mean divided by the degrees of freedom for the within-groups population variance estimate. (10-1) SSRows = g1MRow - GM22 The sum of squared deviations for rows is the sum of each score’s row’s mean’s squared deviation from the grand mean. (10-3) SSInteraction = g31X - GM2 - 1X - M2 - 1MRow - GM2 - 1MColumn - GM242 The sum of squared deviations for the interaction is the sum of the squares of each score’s deviation from the grand mean minus its deviation from its cell’s mean, minus its row’s mean’s deviation from the grand mean, minus its column’s mean’s deviation from the grand mean. (10-4) SSWithin = g1X - M22 The sum of squared deviations within groups (within cells) is the sum of each score’s squared deviation from its cell’s mean. (11-1) r = gZXZY N The correlation coefficient is the sum, over all the people in the study, of the product of each person’s two Z scores, then divided by the number of people. (12-1) Yn = a + 1b21X2 A person’s predicted score on the criterion variable equals the regression constant plus the result of multiplying the regression coefficient by that person’s score on the predictor variable. (13-1) �2 = g 1O - E22 E Chi-square is the sum, over all the categories or cells, of the squared difference between observed and expected frequencies, divided by the expected frequency. (13-3) E = aR N b1C2 A cell’s expected frequency is the number in its row divided by the total, multiplied by the number in its column. 1. Updates in content, examples, boxes, and controversies provide fresh learning material and reflect recent research, and the Using SPSS sections are updated to reflect SPSS Version 19. 2. The correlation chapter has been reworked to help students better understand the logic of correlation coefficients by using the more intuitive formula for calculating correlation coefficients based on Z scores. 3. To strengthen the instructor’s resource materials, full lecture outlines and multiple teaching examples (in addition to what is in the text) for classes based on each chapter have been placed into PowerPoint slides to allow quick and convenient downloadable lectures. 4. A full MyStatLab™ has now been developed specifically for this text and can be bundled at no extra charge to students. MyStatLab provides a rich and flexible set of course materials, featuring problems and essay questions (versions of those in the text as well as additional ones) that students can use to perfect their understanding and instructors can assign for online homework, quizzes, and tests. In addition, we are very excited about the following innovations: For instructors, MyStatLab features: Powerful homework and test manager Comprehensive gradebook tracking Complete online course content Custom exercise and exam builder For students, MyStatLab features: Interactive tutorial exercises Mini-lectures