Pay gap: Webliography assignment

Pay gap: Webliography assignment ORDER NOW FOR CUSTOMIZED AND ORIGINAL ESSAY PAPERS ON Pay gap: Webliography assignment Post one question that you had related to the material this week. Conduct research and provide the answer to the question you posted. Be sure to provide the source. Pay gap: Webliography assignment discussion.docx Week 1, Discussion 1 Data Characteristics/ Descriptive Statistics/Probability/ Descriptive Statistics Data Characteristics / e Michael Wetzel BUS 308 Statistics for Managers Instructor: Donald Platine June 27, 2017 Data Characteristics/ Descriptive Statistics/Probability Part two: Data Characteristics In the BUS308 company, the question revolves around if the males and females a=are paid equally for equal work. While there looks like there can be a correlation, we cannot be sure unless we utilized statistically sampling in excel. When evaluating the data, we concluded that we Cannot reject Null Hypothesis because P > 0.05 (The means are the same). The t-test resulted in a P of .377993. This means we are not able to assume there is a relationship. I found this interesting when evaluating the data, because it there seemed to be a relationship; however, you can never assume! Nominal level data are represented by numbers and they are used to clarify the data. However, words letters and alpha-numeric symbols may also be used. The interval level data does many things. It classifies and orders measurements. Additionally, it specifies the distance between the intervals. Ratio level of measurement is like interval; however, you can use a value of zero. The reason that students often confuse using gender codes coded 0 for male and 1 for female for interval or ratio data level revolves around one idea. Interval level data measures the differences between sequential data points. Using 0 and 1 for male and female is not appropriately identified as nominal level data because students associate internal with numerical values. Intervals revolves around the idea that intervals are equal and meaningful, with meaningful being key. Pay gap: Webliography assignment Also, nominal level data is qualitative, while interval and ratio are considered quantitative. Understanding this is important for this and for the real world. Knowing the kinds of data that are being used is important because it will identify the kinds of statistical sampling analysis completed on the data. Part Three: Descriptive Statistics In business reports, information is provided on the mean or average value for a measure. However, the average alone is not enough information to make an informed judgment about the results. When averaging data, there is an assumption being made that that everything is scaled the same. More factually, the information operates using a possible different scale. For this reason, averaging lacks interpretation. When using statistical and descriptive analysis in business, there is more valuable information at hand. You can make interpretations on your own based on the data. This can be done using statistical theories like standard deviation and distribution. While the average may tell us that the average maple leaf is a certain diameter, knowing the mean with a standard deviation allows for a better understand of what the mean truly identifies. If the standard deviation is large, we may know the leaf really can vary in size; however, if the deviation is small then the mean may be an alright interpretation. Descriptive statistics provides a representation of an entire population or sample better than averaging. It can measure variability, tendencies and other useful tools. Ultimately, descriptive statistics help describe and understand the features within the data. When analyzing potential marketing regions, using descriptive statistics can help understand the sample of the population for an area. If we are looking for specific qualities of a geographical area with respect to the population, the average will not be useful for the task. Part Four: Probability Considering the salary outcomes in our sample results in a probabilistic sample rather than a completely accurate and precise reflection of the population change how we interpret the sample statistic outcomes. In our sample, one thing to think about revolves around grouping. Probability sampling that utilizes random sampling. Pay gap: Webliography assignment This means that there must be an equal chance for each part of the population to be selected. The use of sampling may not result in the correct assumption of the populations. Due to this, we create an error coefficient to mitigate the risk of sampling in error. Additionally, we must take into consideration the standard deviation aspect. One way you can view this in your life would be using a certain product. The different between all the products and a sample may draw many different conclusions. Reference: Sauro, J. (n.d.). Fundamentals of Statistics 1: Basic Concepts :: Nominal, Ordinal, Interval and Ratio. Retrieved June 28, 2017, from http://www.usablestats.com/lessons/noir (Links to an external site.)Links to an external site. Week 1 Lecture 1. Data Characteristics- Interval. … Get a 10 % discount on an order above $ 100 Use the following coupon code : NURSING10

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