...Inferential Statistics QNT/561 September 1, 2014 INFERENTIAL STATISTICS SAT scores from 48 students in a low-performing district were analyzed and a descriptive statistical analysis performed. These students were given individualized SAT coaching and their scores after coaching were compared and analyzed against their scores prior to receiving the individualized coaching. Based on the results of that analysis, we now want to determine whether the findings are indicative of the entire population of SAT taking individuals. Hypothesis: Ho=Individualized SAT coaching did not result in an increase in SAT scores. H1=Individualized SAT coaching did result in an increase in SAT scores. Inferential Statistics Distribution: Normal Regression Statistics | Multiple R | 0.985001 | R Square | 0.970227 | Adjusted R Square | 0.96958 | Standard Error | 13.59259 | Observations | 48 | ANOVA | | | | | | | df | SS | MS | F | Significance F | Regression | 1 | 276957.9 | 276957.9 | 1499.026 | 9.38E-37 | Residual | 46 | 8498.895 | 184.7586 | | | Total | 47 | 285456.8 | | | | | Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | Intercept | -148.751 | 31.54092 | -4.71611 | 2.26E-05 | -212.239 | -85.2619 | -212.239 | -85.2619 | X Variable 1 | 1.133406 | 0.029274 | 38.71726 | 9.38E-37 | 1.074481 | 1.192331 | 1.074481 | 1.192331 | t-Test: Paired Two Sample for Means | | | | | Variable...
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...Descriptive and Inferential Statistics Statistics are all-around and used in everyday life. Statistics are used to describe how effective a medication is for a certain disorder to what the most popular color is in the United States. According to Aron, Aron, and Coups, 2009, “statistics is a method of pursuing truth. As a minimum, statistics can tell you the likelihood that your hunch is true in this time and place and with these sorts of people” (p. 2). Psychologist use two branches of statistics to summarize his or her results and those are descriptive and inferential statistics. This paper will discuss the function of statistics, what descriptive and inferential statistics are, and the relationship between descriptive and inferential statistics. Statistics are used in almost every branch of study and is found behind the scenes in many of our normal daily activities. From economic to scientific studies, statistics are utilized in one way or another. Statistics are an essential part of understanding information and expanding knowledge base and is encompasses almost all aspects of enquiry ("7 Most Essential Functions Of Statistics", 2012). Statistics have many functions that we utilize;statisticsprovides for a better understanding of phenomenon of nature and helps in proper and statistical planning in all forms of study. Using statistics helps in collecting useful quantitative data and also aids in presenting difficult or confusing data in an understandable way. Statistics facilitate...
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...analyzer will incorporate both descriptive and inferential statistics to evaluate his or her results and create a credible conclusion. Descriptive statistics provides information focused on an immediate group of data. After defining what needs to be analyzed, the descriptive statistics will help the analyzer abridge the data to a more meaningful and comprehendible form, which will then provide patterns in his or her research that, will provide a foundation to his or her thesis. For example, a person could use descriptive statistics to evaluate the answers on an exam taken by 400 American students, and use descriptive statistics to determine the overall performance of the 400 students at that school. By using descriptive statistics, the analyzer can use his or her findings, to provide useful information regarding which subjects students need to improve most in, and which minority group or grade level are grasping the educational tools provided at the school more effectively, then those not grasping the provided educational tools and still need more room for improvement. While descriptive statistics helps an analyzer assess an immediate group of data from a single population, inferential statistics allow an analyzer to collect data using bits and pieces of samples which are portions of a collection of data focusing on the group or population of interest in which the analyzer research is concentrated on at the time. Inferential statistics will allow the analyzer to create a conclusion...
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...Descriptive and Inferential Statistics Presentation Tony Roberson, Amani Wilson, Deandra Cobb, and Lysa Satterwhite PSY 315 November 11, 2013 Melinda Waife Descriptive and Inferential Statistics Presentation Click on link below to review Team D’s presentation. http://prezi.com/sz-i9ukpbarl/?utm_campaign=share&utm_medium=copy Tony’s Presentation Speaker Notes: Introduction: Please review Prezi Source: Flickr User "unity_creative" To understand the simple difference between descriptive and inferential statistics, all you need to remember is that descriptive statistics summarize your current dataset and inferential statistics aim to draw conclusions about an additional population outside of proposed data (eCaro, 2003). Deandra Statistics in Psychology and its function cannot be taken lightly. The importance ofthe development of psychology would not have been realized if statistics did not play such a crucial role. Important components such as inferential statistics and interactions are dynamic in the study of associations, and affiliations that are essential in psychology.Statistic is the exact phenomenon of nature and it helps in providing a better understanding. Statistics helps in the effectiveness and planning of statistical analysis in any field of study. Furthermore, helps in applicable quantitative data and in presenting complex data in a suitable level, diagrammatic and graphic form for a clear comprehension of the data. Amani Wilson Speaker Notes...
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...Advance Inferential Statistics [Name] [Course] [Tutor] [College] [Date] Understand the concepts of Binary Logistic Regression Logistic regression is essential in predicting a categorical variable present in a set of variables that are predictors. During Logistic regression, categorical dependent variable which is the discriminant function is used when all the predictors that are present are continuous and distributed in a nice way. The binary logic regression has become the most preferred data analysis method that describes the relationship between response variable and an explanatory variable that and it is usually used where a variable follows binomial distribution. Assumptions of binary logistic regression Among the assumptions applied in the application of binary logistic regression is that logistic regression usually does not assume a relationship that is linear between the dependable and undependable variables. It is a must for the dependable variable to be a dichotomy i.e. must have two categories. It is also not required that the independent variables to be an interval, distributed in a normal way, linearly related, or even have linear variance within specific groups. Another assumption is that large samples are most important in this regression because it has a maximum likelihood of coefficients of large sample estimates. It is usually recommended that one should have a linear regression of 50 cases and above per predictor...
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...Advance Inferential Statistics [Name] [Course] [Tutor] [College] [Date] Understand the concepts of Binary Logistic Regression Logistic regression is essential in predicting a categorical variable present in a set of variables that are predictors. During Logistic regression, categorical dependent variable which is the discriminant function is used when all the predictors that are present are continuous and distributed in a nice way. The binary logic regression has become the most preferred data analysis method that describes the relationship between response variable and an explanatory variable that and it is usually used where a variable follows binomial distribution. Assumptions of binary logistic regression Among the assumptions applied in the application of binary logistic regression is that logistic regression usually does not assume a relationship that is linear between the dependable and undependable variables. It is a must for the dependable variable to be a dichotomy i.e. must have two categories. It is also not required that the independent variables to be an interval, distributed in a normal way, linearly related, or even have linear variance within specific groups. Another assumption is that large samples are most important in this regression because it has a maximum likelihood of coefficients of large sample estimates. It is usually recommended that one should have a linear regression of 50 cases and above per predictor...
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...Descriptive and Inferential Statistics PSY/315 Statistical Reasoning in Psychology September 21, 2013 Dr. Nancy Walker Descriptive and Inferential Statistics Statistics is “a branch of mathematics that focuses on the organization, analysis, and interpretation of a group of numbers” (Aron, Aron, & Coups, 2009, p. 2). However, just the mention of statistics makes people nervous, although when properly understood, many of the questions statistics tries to answer are very provocative and challenging. Statistics are a collection of information and, data that helps test the theory something is happening or will happen again. The functions of statistics are there to help researchers have a better understanding of a phenomenon. Statistics can be used when looking for the truth, if you have ever had a hunch about something, was it confirmed? Yes the hunch was confirmed. Statistics help researchers with data by using math and working with a group of numbers. Statistics studies variables, characteristics that have different values, values, possible number that a score can have, and score one person value of a variable (Aron, Aron, & Coups, 2009). Descriptive and inferential statistics are to evaluate results and enable one to make a conclusion. Descriptive statistics are a way to describe data (Laird Statistics, 2013), as well as to “summarize and describe a group of numbers from a research study,” whereas, inferential statistics are used to “draw conclusions and...
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...Descriptive and Inferential Statistics Paper Casie Thibeault PSY/315 July 27, 2013 Michelle A. Williams, PhD Descriptive and Inferential Statistics Paper The very word “statistics” seems to produce anxiety in most students - anxiety produced from its connection to mathematics. The first step in controlling anxiety is to understand the connection and just how useful statistics can be for comprehending information that has been gathered. A statistic is a representation of information, and its function is to help researchers either to organize, summarize, or understand data. The ability to describe data is essential when gathering statistics. Statistics can be broken down into two basic types: descriptive statistics and inferential statistics. Descriptive statistics are a summary of information that makes the data presented more easily understood. The descriptive method is limited to only the population in which the researcher is dealing with, and only describes that particular group (Purdue OWL, 1995-2013). Inferential statistics offers a more detailed conclusion regarding the hypothesis. A benefit of the inferential method is that it can be used to take a broader view of populations, making it possible to draw conclusions about sizeable groups of people (Purdue OWL, 1995-2013). In a nutshell, the simple way to distinguish between the two would be that descriptive statistics summarize and inferential statistics draw conclusions. Both descriptive and inferential statistics...
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...Descriptive and Inferential Statistics Paper Terrance Douglas, Katie Faiman, Marika Schlindwein, Christyl Schoultz, & Samantha Sisk PSY/315 February 3, 2013 Dr. Deborah Suzzane Descriptive and Inferential Statistics Paper Have you ever noticed that we just keep moving forward? There are countless, unseen individuals who make this happen each day, but how do they operate? How do they accomplish all of this? We live in a complex world. Behind the scenes, researchers are steadily developing new theories and testing their outcome. For them, statistics serves a very different purpose. In the next few paragraphs, the role of statistics is explained as their role in the psychological community. Statistics itself is then further subdivided into two different methodologies; descriptive and the inferential (Aaron & Aaron & Coups, 2009). Each method utilizes data for a different purpose, and in each method, data may be gathered differently. Lastly, an example of each of the two types of statistics which helps the reader to distinguish clearly between the descriptive and inferential types of statistics which researchers use to conduct their work. It will further be shown how the two methods of statistics relate to each other in research. It is by understanding the two different roles of each of these types of statistics that researchers are able to gather meaningful data, which is testable and provable and keeps us on a forward moving trajectory...
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...8A1 This assignment lets you explore a quasi-experimental model using ANCOVA data analytical approach. By doing this data analysis project, you will understand a new quantitative research model when randomized sampling is not a choice. Specifically, you will develop analytical skills to use covariate to control for or partial out effects of pre-existing differences carried by sampling. To complete the assessment, answer each question, providing IBM SPSS analysis when necessary to support your answer. For this assignment, use the small batch of data provided by Warner's textbook on page 724. These are hypothetical data. We will imagine that a three-group quasi-experimental study was done to compare the effects of three treatments on the aggressive behavior of male children. Xc, the covariate, is a pretest measure of aggressiveness: the number of aggressive behaviors emitted by each child when the child is first placed in a neutral playroom situation. This measure was done prior to exposure to the treatment. Children could not be randomly assigned to treatment groups, so the groups did not start out exactly equivalent on aggressiveness. The dependent variable, Y, is a posttest measure: the number of aggressive behaviors emitted by each child after exposure to one of the three treatments. Treatment A consisted of three different films. The A1 group saw a cartoon animal behaving aggressively. The A2 group saw a human female model behaving aggressively. The A3group saw a human male...
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...Goudy RES/351 July 6, 2015 Tracy Sipma Descriptive statistics Descriptive statistics suggests a straightforward quantitative outline of a data-set which has been gathered. It helps us comprehend the experimentation or data-set in-detail and tells people concerning the mandatory details that help show the data perceptively. Descriptive statistics, we just convey exactly what the data reveals and tell us. Most of the statistical averages and numbers we estimate are essentially illustrative averages. For instance the Dow Jones Industrial tells us about the typical performance of select firms. The grade-point avg. tells us about the typical performance of a pupil in school. The GDP growth rate tells us about the typical performance of a state. Therefore illustrative statistics attempts to catch a sizable group of observations and offers us some concept concerning the data-set. Descriptive statistics aims to describe data set information with summary graphs and tables (Linda Hollis, n.d.). Inferential Statistics Inferential statistics includes drawing the correct conclusions from your statistical evaluation that's been performed using descriptive data. Ultimately, it really is the inferences that make studies significant and this element is dealt with-in inferential data. Most forecasts of the potential and generalizations of a population by analyzing a smaller sample come under the scope of inferential statistics. Many social sciences experiments offer with analyzing a little...
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...BSHS 382 Week 5 Learning Team Statistics and Hypothesis Testing Presentation To Buy This material Click below link http://www.uoptutors.com/BSHS-382/BSHS-382-Week-5-Learning-Team-Statistics-and-Hypothesis-Testing-Presentation Prepare a 10- to 15-slide Microsoft® PowerPoint® presentation on statistics and hypothesis testing. This is a Microsoft® PowerPoint® presentation with speaker notes. Anorexia, as described on p. 383 of Statistics Enchiladas, as described on pp. 113 and 114 of Statistics FL Student Survey, as described on pp. 22 and 23 of Statistics Georgia Student Survey, as described on pp. 22, 23, and 151 of Statistics Olympic High Jump, as described on pp. 124, 125, and 128 of Statistics Introduction o Introduce the Learning Team members and the data set. o Briefly explain how the data was gathered and identify the study population. Descriptive Statistics o Define descriptive statistics and list the various descriptive measures. o Explain how descriptive statistical analysis increases understanding of the data. o Include an original graph created with StatCrunch that uses at least one descriptive statistical measure to illustrate the data set. Inferential Statistics o Define statistical inference and include and explain at least one original inferential statistical calculation. o Use StatCrunch to check the calculation and show the steps in your presentation. o Explain how inferential statistical analysis increases...
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... Introduction to Statistics LEARNING OBJECTIVES The primary objective of chapter 1 is to introduce you to the world of statistics, enabling you to: 1. Define statistics. 2. Be aware of a wide range of applications of statistics in business. 3. Differentiate between descriptive and inferential statistics. 4. Classify numbers by level of data and understand why doing so is important. CHAPTER OUTLINE 1.1 Statistics in Business Best Way to Market Stress on the Job Financial Decisions How is the Economy Doing? The Impact of Technology at Work 1.2 Basic Statistical Concepts 1.3 Data Measurement Nominal Level Ordinal Level Interval Level Ratio Level Comparison of the Four Levels of Data Statistical Analysis Using the Computer: Excel and MINITAB KEY TERMS census ordinal level data descriptive statistics parameter inferential statistics parametric statistics interval level data population metric data ratio level data nominal level data sample nonmetric data statistic nonparametric statistics statistics STUDY QUESTIONS 1. A science dealing with the collection, analysis, interpretation, and presentation of numerical data is called _______________. 2. One way to subdivide the field of statistics is into the two branches...
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...Statistics: Highly Informative Latosha Greer BUS308: Statistics for Managers Instructor Hayes June 1, 2014 In this essay I am aim to discuss the differences between descriptive statistics and Inferential statistics and the reasons why we use them. I will also discuss hypothesis development and testing, when to select the appropriate statistical test, and how to evaluating statistical results. In this class I learned the difference between descriptive statistics and inferential statistics. We use descriptive statistics to measure and analysis data. There are a number of reasons why we use Descriptive statistics. We use it, because Descriptive statistics numerical summaries measure the central tendency of a data set, it can include graphical summaries that show the spread of the data, and they provide simple summaries about the sample that help interpret and analyze data. First, there are a number of reasons why we use descriptive statistics we use it because descriptive statistics numerical summaries that either measure the central tendency of a data set. In business therefore descriptive statistics helps in making conclusions about various issues and therefore helps in making decision. Description statistics is the first step in analyzing data before making inferences of data, therefore it is important in analyzing any data collected that will help in describing the characteristics of data collected. There are three measurements that we tend to use. One measurement...
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...Institute of Management Sciences Peshawar Bachelors in Business Studies Course Plan Course Title: Statistics for Business Instructor: Shahid Ali Contact Email shahid.ali@imsciences.edu.pk Semester/Duration: 16 Weeks Course objectives : To introduce students to the concepts of statistics and to equip them with analytical tools to be used in business decision making. The course is intended to polish the numeric ability of the students to identify business problems, describe them numerically and to provide intelligible solutions by data collection and inferential principles. Course pre-requisites Intermediate statistics Attendance Policy: Late arrivals are highly discouraged. Any student coming late to a class late by 5 minutes after the scheduled start time will be marked as absent for the day. The teacher reserves discretion, however, to allow or disallow any student, to sit in the class in case of late arrivals. Attendance is not be entertained once the attendance register is closed. Class Project Students will be divided in groups for a class project. Each group will have to nominate a group leader. The details of the project will be made available to the group leader. Class Presentations Each student will have to make at least one individual presentation and one group presentation in the class. The group presentation will be on the project explained earlier. The individual presentations will...
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