Submitted By Marameero

Words 856

Pages 4

Words 856

Pages 4

Graphical and Numerical Representation for the Population:

Figure (1): A histogram showing the distribution of grades of the first year students of 2014.

Interpretation:

* The Histogram is negatively skewed ( it has a long tail extending to the left) which means that the majority of students got grades between 15 and 30 while a small number of them got low grades. This more emphasized by calculating the coefficient of skewness for this variable which is -1.02. * The Histogram is also Unimodal and the modal class is 20- which has a frequency of 101 which means that 101 students got grades from 20 to 25 with a percentage of 43.72% of the total population. (See table 2 in the Appendix). The Mode for this distribution is unique which approximately equals 23. * The mean of such distribution is 21.303 (See Table 1 in the Appendix) which means that the sum of deviations from this number “21.303” equals zero. Furthermore, since this distribution is negatively skewed we previously expect that mean<median<mode. * The distribution appears to be variable where the standard deviation when calculated is 5.014 indicating the variability of such distribution where we have students score zero and others score 30.

To further conclude more information about the grades we can obtain the boxplot.

Figure (2): A Boxplot for the grades in S101 in the year 2014-2015

Interpretation:

* The boxplot emphasizes the fact…...

...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......

Words: 1232 - Pages: 5

...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......

Words: 1507 - Pages: 7

...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......

Words: 1196 - Pages: 5

...Descriptive Statistics Analysing Age and Monthly Income 26 October 2012 Ana Rita Costa, n.º 152112179 Cátia Raquel Reais Ferreira de Araújo; n.º 152112188 INDEX 1. Introduction 3 2. Age 4 3. Monthly income 8 4. Association between variables 12 5. Conclusion 13 1. Introduction This work intends to address the request to describe two different data sets – one with observations for a discrete random variable and another with observations for a continuous random variable – according to the Business Statistics course theoretical framework. Through the use of the Descriptive Statistics’ tools – frequency tables, numerical descriptive measures and charts – we aim to examine, describe and compare distinctive aspects of a given sample. Therefore, we have chosen to analyse the age of the sample’s individuals as a discrete variable and, as a continuous variable, their monthly income. Bearing in mind the widely association between age and earnings, we decided to scrutiny such link. In order to satisfy this purpose we acceded a BES (Banco Espírito Santo) database related to savings. From there we collected information on fifty-three individual concerning age, monthly income, gender and level of education. We looked to select a broad and diversified sample likely to provide us with an accurate representation of the population. For the intended study we preceded to organize and simplify the presentation of......

Words: 2174 - Pages: 9

...probability report were the qualitative variables gender and quantitative variable extrinsic. The probabilities below show the probability for gender, employee’s tenure with the company, and the percentage of employees that are in different departments. Use of Statistics and Probability in the Real World We us probability in our everyday lives we are just un-ware of when it’s being used such as when watching the new and the weather man says there is a 90% chance (probability) that it will rain. When bets are made the person making the bet estimates the probabilities of a teaming winning, also when flipping a corn there is 50/50 chance (probability) of getting tails or heads on the corn toss. In school statistics are used for test scores such as the average score on test is 75% out of 100% for a group of 60 students. We can generalize that each student will mostly likely get a 75/100 on the test. The Value of Statistics Statistics play an important role in fields of people’s activities. Statistics can determine unemployment, housing, or population growth in a country (Stephanie, 2010). Statistics holds a positions in a lot of fields such as mathematics, chemistry, biology, and physics. So the application of statistics is very wide. Distributions A distribution table can be used to organize data to where it makes sense (DeGroot, 2011). Information on a distribution table can be used by AIU see the number of males and females that participated in the survey and how they......

Words: 817 - Pages: 4

...Chapter 2 Descriptive Statistics: Tabular and Graphical Methods Summarizing Qualitative Data Summarizing Quantitative Data Exploratory Data Analysis Crosstabulations and Scatter Diagrams Summarizing Qualitative Data Frequency Distribution Relative Frequency Percent Frequency Distribution Bar Graph Pie Chart Frequency Distribution A frequency distribution is a tabular summary of data showing the frequency (or number) of items in each of several nonoverlapping classes. The objective is to provide insights about the data that cannot be quickly obtained by looking only at the original data. Example: Marada Inn Guests staying at Marada Inn were asked to rate the quality of their accommodations as being excellent, above average, average, below average, or poor. The ratings provided by a sample of 20 guests are shown below. Below Average Average Above Average Above Average Above Average Above Average Above Average Below Average Below Average Average Poor Poor Above Average Excellent Above Average Average Above Average Average Above Average Average Example: Marada Inn Frequency Distribution Rating Frequency Poor 2 Below Average 3 Average 5 Above Average 9 Excellent 1 Total 20 Relative Frequency Distribution The relative frequency of a class is the fraction or proportion of the total......

Words: 2138 - Pages: 9

...3,915 2,706 3,430 3,518 17 18 18 18 18 18 19 19 19 19 20 20 21 21 21 80 81 82 83 84 14 6 77 41 37 85 86 87 88 89 90 91 7 89 19 62 38 60 Nim's Island Indiana Jones and the 3 Kingdom of the Crystal Skull 82 The Reader Journey to 26 the Center of the Earth 2 Iron Man Dr. Seuss' 10 Horton Hears a Who! 12 Gran Torino Slumdog 16 Millionaire 5 WALL-E 100,137,835 317,101,119 4,264 21 92 93 168,051 21,018,141 98,618,668 45,012,998 271,720 360,018 63,087,526 34,194,407 101,704,370 318,412,101 154,529,439 148,095,302 141,319,928 223,808,164 1,203 2,830 4,154 3,961 3,045 2,943 3,992 22 22 22 25 27 28 28 94 95 96 97 98 99 100 1 The Dark Knight 158,411,483 533,345,358 4,366 33 DESCRIPTIVE STATISTICS Opening Gross Mean Standard Error Mode #N/A 26,160,050 2,334,918 #N/A Total Gross 85,228,635 7,405,866 Theaters 2,958 73 2798 Standard Deviation Range Minimum 23,349,183 158,287,970 123,513 74,058,662 504,700,545 28,644,813 735 3,679 687 Q1 Median 13,314,517 19,066,030 38,020,299 61,833,338 2,627 3,029 Q3 Maximum 61,457,841 158,411,483 102,098,073 533,345,358 3,470 4,366 The data tells me that the success of movies varies wildly. For example, consider the the "total gross" variable The movie that brought in the least was about half of the median, where the movie that brought in the most was While most movies bring in a modest amount, a few blockbusters do really well. The mean total......

Words: 1960 - Pages: 8

...Descriptive Statistics kWh 1st Hour Operational Day This data set has a p-value of much less than .05 so it is classified as skewed, or not normally distributed. In this case the Median and the IQR are better indicators of the distribution. Central Tendency: Mean = 113.76; Median = 108; Mode = 128 Dispersion: Standard Deviation = 39.05; IQR = 60; Range = 169 Number: n = 147 Min/Max: 53/222 Overnight Low OAT in F° This data set is distributed normally. Central Tendency: Mean = 66.3; Median = 65.3; Mode = 67.8 Dispersion: Standard Deviation = 7.9; IQR = 11.7; Range = 36.9 Number: n = 147 Min/Max: 48.9/85.8 Confidence Interval: Lower = 65.04; Upper = 67.62 OAT Strata OAT < 70; OAT ≥ 70 Descriptive Statistics Interpretation kWh 1st Hour Operational Day The 60 minutes from 7:00a – 7:59a combine to make the first hour of the operational day for this school. The number of kWh consumed as measured by the electric meter and collected by the website, MYPVDATA.com, are tabulated for each day in the time period, August 1 through October 31. This data is taken from each of these time periods over three years, 2012 through 2014. This gives us a sample of 147 individual electric meter readings for the electricity consumed in the 7:00a hour on operational days. The kWh is a measurement of electrical demand. Things that consume electricity are for instance, air conditioners and heaters, lights and other peripheral equipment. The electricity......

Words: 944 - Pages: 4

...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......

Words: 1193 - Pages: 5

...Descriptive Statistics Pain Study “The kappa opioid nalbuphine produces gender-and dose-dependent analgesia and antianalgesia in patients with postoperative pain” was a study that was performed to observe gender-specific patient response to varied doses of nalbuphine, an opioid pain medication, following oral surgery (Gear, Miaskowski, Gordon, Paul, Heller, & Levine, 1999). In this study, the researchers asked participants to rate their pain on a 10 cm visual analog scale (VAS) just before drug administration to obtain a baseline measurement, and again at 20 minute intervals thereafter (Gear et al., 1999). The demographic characteristics and descriptive statistics of the 131 participants are provided in Table 1 of the study (Gear et al., 1999). To aid in interpretation of the data collected in the research experiment, the researchers provide the reader with information using both ratio and ordinal data measurements. The weight of the participants is given as a mean, or average, and is considered ratio measurement. This is important data because weight is a variable that is considered when calculating dosage requirements. For each dose of pain medication given, as well as the placebo, the weight in kilograms for both men and women is averaged in the table. The data appropriate and meaningful since the average weight of participants in each dose category is similar save for the weight differences between men and women. Ratio measurement is considered the......

Words: 2022 - Pages: 9

...weight. (b) What sample size would be necessary to estimate the true weight with an error of } 0.03 grams with 90 percent confidence? (c) Discuss the factors which might cause variation in the weight of Tootsie Rolls during manufacture. (Data are from a project by MBA student Henry Scussel.) Tootsie Answers: a) Confidence intervals are used to find a region in which we are 100 * ( 1 - α )% confident the true value of the parameter is in the interval. In order for the Confidence Interval to be valid you must have data from a normal distribution, at least if you are using the method here. If you do not have normal data then this type of confidence interval is not valid. To clear up the notation I will use here. "t" is the test statistic and "t_(n-1)" is a Student t random variable with n - 1 degrees of freedom, e.g. a Student t random variable with 18 degrees of freedom is denoted as t_18.For small sample confidence intervals about the mean you have: xBar ± t * sx / sqrt(n) where xBar is the sample mean t is the t - score with n - 1 degrees of freedom such that α% of the data in the tails, i.e., P( |t_(n-1)| > t) = α sx is the sample standard deviation n is the sample size The sample mean xbar = 3.3048 The sample standard deviation sx = 0.1319889 The sample size n = 10 The t score for a 0.9 confidence interval is the t score such that 0.05 is in each tail. t = 1.833113 The confidence interval is: ( xbar - t * sx / sqrt( n ) , xbar + t *......

Words: 917 - Pages: 4

...Chapter 2: Descriptive Statistics Prerequisite: Chapter 1 2.1 Review of Univariate Statistics The central tendency of a more or less symmetric distribution of a set of interval, or higher, scaled scores, is often summarized by the arithmetic mean, which is defined as [pic]. (2.1) We can use the mean to create a deviation score, [pic] (2.2) so named because it quantifies the deviation of the score from the mean. Deviation is often measured by squaring, since it equates negative and positive deviations. The sum of squared deviations, usually just called the sum of squares, is given by [pic] (2.3) Another method of calculating the sum of squares was frequently used during the era that preceded computers when students would work with calculating machines, [pic] (2.4) Regardless whether one uses Equation (2.3) or Equation (2.4), the amount of deviation that exists around the mean in a set of scores can be averaged using the standard deviation, or its square, the variance. The variance is just [pic] with s being the positive square root of s2. We can take the deviation scores and standardize them, creating, well; standardized scores: [pic]. (2.5) Next, we define a very important concept, that of the covariance of two variables, in this case x and y. The covariance between x and y may be written Cov(x, y). We have [pic] [pic] (2.6) where the[pic]are the deviation scores for the x variable, and the [pic]are......

Words: 1055 - Pages: 5

...Report Business Research Methods The third homework (about the descriptive statistics) Question 1: Explain the difference of Mobile Contents Use by gender Crosstabs Case Processing Summary | | Cases | | Valid | Missing | Total | | N | Percent | N | Percent | N | Percent | Sex * Music | 300 | 100.0% | 0 | .0% | 300 | 100.0% | Sex * Movie | 300 | 100.0% | 0 | .0% | 300 | 100.0% | Sex * DMB | 300 | 100.0% | 0 | .0% | 300 | 100.0% | Sex * Phone Decorating | 300 | 100.0% | 0 | .0% | 300 | 100.0% | Sex * Sport | 300 | 100.0% | 0 | .0% | 300 | 100.0% | Sex * Game | 300 | 100.0% | 0 | .0% | 300 | 100.0% | Sex * MMS | 300 | 100.0% | 0 | .0% | 300 | 100.0% | Sex * Adult | 300 | 100.0% | 0 | .0% | 300 | 100.0% | Sex * Animation | 300 | 100.0% | 0 | .0% | 300 | 100.0% | Sex * Mobile banking | 300 | 100.0% | 0 | .0% | 300 | 100.0% | Sex * Map | 300 | 100.0% | 0 | .0% | 300 | 100.0% | Sex * Stock Trading | 300 | 100.0% | 0 | .0% | 300 | 100.0% | Sex * Chatting | 300 | 100.0% | 0 | .0% | 300 | 100.0% | Sex * News/Weather | 300 | 100.0% | 0 | .0% | 300 | 100.0% | Sex * Music Crosstab | | Music | Total | | 0 | 1 | | Sex | 1 | Count | 91 | 97 | 188 | | | % within Sex | 48.4% | 51.6% | 100.0% | | | % within Music | 65.0% | 60.6% | 62.7% | | 2 | Count | 49 | 63 | 112 | | | % within Sex | 43.8% | 56.3% | 100.0% | | | % within Music | 35.0% | 39.4% | 37.3% | Total | Count | 140 | 160 | 300 | | % within Sex | 46...

Words: 4191 - Pages: 17

... an 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...

Words: 699 - Pages: 3

...Descriptive Statistics University of Phoenix July 18, 2011 RES/341 Descriptive Statistics In the previous weeks we researched the issues that have been affecting the real estate business; such as home prices in which are making it difficult for homes to sale. The current issues that are affecting the housing market in today’s society have to do with homes being over priced due to size, location, and square footage. In the past weeks Learning Team C had to research the problems in the housing market to determine the reasons why homes that are similar in size tend to be more expensive than others and the factors that go into these prices. The research problem that Learning Team C encountered has to do with looking at: 1. Price, 2. Bedrooms, 3. Size, 4. Pool, 5. Distance, 6. Township, 7. Garage, and 8. Baths, to determine why some of the listed homes are more expensive than others homes in the area. In week three we turned the research over to researching peer-reviewed articles to get an even clearer picture of the whole aspect of real estate, which included; faulty work from appraisers, estimating value of homes, and how size play a major role in the price of a home. Moving on into week four, Learning Team C will evaluate all the data from the previous weeks and draw a conclusion based on all current research finding of why similar homes tend to be more expensive than others. Frequency Distribution The following graphics and data analysis will identify the......

Words: 1999 - Pages: 8