1699 Words7 Pages

Chapter 12 introduces the reader to the true definition of statistics, without scaring them half to death. The book breaks statistics down in two parts: descriptive and inferential. The type that is dealt with in this chapter is descriptive statistics. The simple definition of descriptive statistics are that they are just numbers in different forms, for example, percentages, numerals, fractions, and decimals. The book gives an example of a grade point average being a descriptive statistic.
It is becoming increasingly important for classroom teachers to be able to understand and interpret statistics because of increasing calls for acountablity. Being able understand various types of statistics, there uses and limitations, will put the educator who does at an advantage. Instead of just averaging grades, there are important questions that every educator should want to know the answers to regarding their classroom. Questions like, how many people are above average and how many scored above the cutoff passing score, are questions that can't be answered without some working knowledge of statistics.
The bar graph explanation was pretty clear in the chapter, but that might be just because it's the most frequently used graph to convey statistical data. Everyone is familiar with the bar graph, but when it comes down to frequency polygons things get a little fuzzy.
Chapter 13 explains how distributions can have the same values for the mode, median, and mean but are different in the way the scores are spread out. The variability estimate helps determine how compressed or expanded the distributions are.
The range is the easiest way to estimate variability and its determined from subtracting the lowest score from the highest score. In the case of the range, things can get thrown off if an extreme score is present. One way of preventing this from happening is to use the semi-interquartile range. This score is determined by taking the middle 50% of the scores in a distribution. The upper 25% and the lower 25% are not entered into its final computation.
Standard deviation is an estimate of variability that accompanies the mean in describing a distribution. You are taking a look at each distribution to see how far away each score deviates from the mean.
The normal distribution is a type of symmetrical distribution that is mathematically determined and has fixed properties. It is basically used as a model to base statistical decisions. These are methods that can most definitely be used in the classroom when analyzing data.

Related

## Designing a Random Number Generator

2071 Words | 9 PagesWhen a bit stream really FAILS BIG, you w... ... middle of paper ... ... of the Utility called TestU01 which has some predefined test suites for sequences of uniform random numbers over the interval (0,1). Conclusion We designed an RNG which is combination of 4 simple generators. we have tested and shown that the final RNG gives uniform distribution and passes 9 different complex tests which suggests that the designed RNG is enough random and can be used for simulation studies or other purposes. Empirical studies also proves that by combining two or more simple generators, by means of a simple operations such as +, -, * or (exclusive-or), provides a composite with better randomness than either of the components[ G. Marsaglia. A current view of random number generators, 1984].

## Statistics Assignment: Grades Sav Data File

635 Words | 3 PagesA negative value indicates a distribution which is more peaked than normal, and a positive kurtosis indicates a shape flatter than normal. An extreme positive kurtosis indicates a distribution where more of the values are located in the tails of the distribution rather than around the mean (Grad pad, 2013). A kurtosis value of +/-1 is considered very good for most psychometric uses, but +/-2 is also usually acceptable (Grad pad, 2013). The above graph shows GPA with a kurtosis of -.811; awhile the final kurtosis is -33.2. The extent to which a distribution of values deviates from symmetry around the mean is the skewness.

## The Confurmability Factor Analysis: An Analysis Of Confirmatory Factor Analysis

1030 Words | 5 PagesIn the table NPAR stands for Number of parameters, and CMIN (x²) is the minimum discrepancy and represents the discrepancy between the unrestricted sample covariance matrix S and the restricted covariance matrix. Df stands for degrees of freedom and P is the probability value. In SEM a relatively small chi-square value supports the proposed theoretical model being tested. In this model the x² value is 334.687 and is small compared to the value of the independence model (3971.586). Hence the x² value is good.

## Assessment Choices in the Classroom

949 Words | 4 PagesLinking instruction and assessment is critical to effective learning. Educators should provide students with various options for learning that include: different ways to learning (style and time), di... ... middle of paper ... ...re provided with ample opportunities to demonstrate their abilities. MI theory is used as formal and informal assessment in the classroom to allow students to be grasp and understand concepts. The use of multiple types of assessments in the classroom yield richer and more qualitative information about a child's achievement. If the ultimate goal is student learning, then there is a place for both standardized testing and authentic assessment using the MI theory in today's classroom.

## The Three Features Of Normal Distribution

1071 Words | 5 PagesIt’s important to understand that the mean does not represent an individual – there may be no individual whose value matches the mean; but the mean is a summary of the entire population. It is easy to calculate: add up all the numbers, then divide by how many numbers there are. The sum divided by the count. The median is almost always more representative of a typical member of a group. If you take all of the numbers in a list, and arrange them from lowest to highest, or vice versa, if there is an odd number, the number at the middle will be the median.

## DWT Architecture

2814 Words | 12 PagesFPGA is used in general in these systems due to low cost and high computing speed with reprogrammable property. 3.2 Lifting Scheme for 1-D DWT using 9/7 Filter The basic idea behind the lifting scheme is very simple; try to use the correlation in the data to remove redundancy [3, 4]. First split the data into two sets (split phase) i.e., odd samples and even samples as shown in Fig. 3.2[1, 2]. Because of the assumed smoothness of the data, we predict that the odd samples have a value that is closely related to their neighbouring even samples.

## Estimation of Population Parameters

1465 Words | 6 Pagesn The variance of the distribution of the sample mean is equal to the variance of the sample mean divided by the sample size. These are true whatever the distribution of the parent population. The Central Limit Theorem allows predictions to be made about the distribution of the sample mean without any knowledge of the distribution of the parent population, as long as the sample is large enough. For this reason, the sample size will be set at 50, which I consider large enough for the distribution of its mean to be normal (according to the Central Limit Theorem). It should not be larger because the aim of this investigation is to carry out a “small scale survey” How / What Data to be Collected The sample will be of the weight of 50 smarties.

## Biometric Iris Recognition: A Literature Survey

1099 Words | 5 PagesExperimental results show that their proposed technique is tolerant to off-axis eye images, specular reflections, non-uniform illumination; glasses, contact lens, hair, eyelashes, and eyelids occlusions. Li, P., et. al [72] also introduce a robust iris segmentation algorithm based on the Random Sample Consensus (RANSAC). According to their experiment, this algorithm can localize the iris boundaries more accurately than the methods based on the Hough transform. Li, P., et.

## Assessment & Grading in the Classroom

1461 Words | 6 PagesHowever, many students freeze under normal testing procedures and may need to be evaluated in another manner. Also, it is important for teachers to understand fair grading procedures so students can best benefit from effective tests. By knowing the main ways of measuring student achievement, and proper formats for grading, students can be evaluated correctly. (Fairtest, 98) There are two main ways of evaluating a student’s work: objective tests and essay questions. Objective testing places emphasis on a precise, efficient focus on a student’s knowledge of defined variables (Kopeikin, 2000).

## education

3942 Words | 16 PagesWhile the process is nearly as important as the product, as educators, we want students to be solving problems appropriately. Parents, administrators, and school board officials (as well as teachers) want to know that students are learning skills that follow the curriculum. Additionally, students need to know that they are solving problems correctly, and if they are not, the teacher needs to determine why that is the case. Evaluation of This Plan Appendix

### Designing a Random Number Generator

2071 Words | 9 Pages### Statistics Assignment: Grades Sav Data File

635 Words | 3 Pages### The Confurmability Factor Analysis: An Analysis Of Confirmatory Factor Analysis

1030 Words | 5 Pages### Assessment Choices in the Classroom

949 Words | 4 Pages### The Three Features Of Normal Distribution

1071 Words | 5 Pages### DWT Architecture

2814 Words | 12 Pages### Estimation of Population Parameters

1465 Words | 6 Pages### Biometric Iris Recognition: A Literature Survey

1099 Words | 5 Pages### Assessment & Grading in the Classroom

1461 Words | 6 Pages### education

3942 Words | 16 Pages