C723 Quantitative Analysis for Business- Final WGU

C723 Quantitative Analysis for Business- Final WGU Leave the first rating Students also studied Terms in this set (93) Save C723 Quantitative Business Analysis ...43 terms rwdixon1993Preview C723 Quantitative Analysis for Busin...93 terms Tori_R8Preview C723 Quantitative Business Analysis ...43 terms alameda11Preview WGU C 114 term Jess Hypothesisis an assumption about a population parameter such as a mean or a proportion null hypothesis (H0)-represents the status quo -states a belief that the population parameter is ≤, =, or ≥ a specific value -believed to be true unless there is overwhelming evidence to the contrary alternative hypothesis (H1)-represents the opposite of the null hypothesis -believed to be true if the null hypothesis is found to be false -always states that the population parameter is >, ≠, or < a specific value two-tail hypothesis testis used whenever the alternative hypothesis is expressed as ≠ one-tail hypothesis testis used when the alternative hypothesis is stated as < or > Type I error-occurs when the null hypothesis is rejected when it is true -when it occurs the producer is looking for a problem in its process that does not exist Type II error-occurs when we fail to reject the null hypothesis when it is not true -when it occurs the customer is getting a product from a process that is not performing properly Correlation analysis-is used to measure both the strength and direction of a linear relationship between two variables -A relationship is linear if the scatter plot of the independent and dependent variables has a straight-line pattern correlation coefficient, r-indicates both the strength and direction of the linear relationship between the independent and dependent variables

population correlation coefficient (ρ)refers to the correlation between all values of two variables of interest in a population confidence interval for the meanis an interval estimate around a sample mean that provides us with a range within which the true population mean is expected to lie confidence levelis defined as the probability that the interval estimate will include the population parameter of interest Student's t-distributionis used in place of the normal probability distribution when the sample standard deviation, s, is used in place of the population standard deviation, σ probability sampleis a sample in which each member of the population has a known, nonzero, chance of being selected for the sample simple random sampleis a sample in which every member of the population has an equal chance of being chosen Sampling erroris defined as the difference between the sample statistic and the population parameter Central Limit Theoremstates that the sample means of large-sized samples will be normally distributed regardless of the shape of their population distributions normal probability distributionis useful when the data tend to fall into the center of the distribution and when very high and very low values are fairly rare exponential distributionis used to describe data where lower values tend to dominate and higher values don't occur very often.uniform distributiondescribes data where all the values have the same chance of occurring Discrete data-Values are whole numbers (integers) -Usually counted, not measured Continuous data-Can potentially take on any value, depending only on the ability to measure accurately -Often measured, fractional values are possible Variancea measure of the spread of the individual values around the mean of a data set expected monetary value (EMV)is the mean of a discrete probability distribution when the discrete random variable is expressed in terms of dollars Probability-a numerical value ranging from 0 to 1 -indicates the chance, or likelihood, of a specific event occurring ExperimentThe process of measuring or observing an activity for the purpose of collecting data

Sample spaceAll the possible outcomes, or results, of an experiment joint probabilityprobability of the intersection of two events mutually exclusiveTwo events cannot occur at the same time during the experiment Conditional probabilitythe probability of Event A occurring, given the condition that Event B has occurred Permutationsare the number of different ways in which objects can be arranged in order Central tendencyis a single value used to describe the center point of a data set z-score-identifies the number of standard deviations a particular value is from the mean of its distribution -has no units Chebyshev's Theorem-states that for any number z greater than 1, the percent of the values that fall within z standard deviations above and below the mean will be at least -applies regardless of distribution

five-number summaryconsists of these five values:

-The minimum value -The first quartile -The second quartile -The third quartile -The maximum value frequency distributionshows the number of data observations that fall into specific intervals Relative frequency distributionsdisplay the proportion of observations of each class relative to the total number of observations Statisticsthe mathematical science that deals with the collection, analysis, and presentation of data, which can then be used as a basis for inference and induction Primary datadata that you have collected for your own use Secondary Datadata collected by someone else Descriptive statisticsCollecting, summarizing, and displaying data Standard Deviation-square root of variance -common measure of consistency in business applications, such as quality control -measures the amount of variance around the mean Law of large numbersstates that when an experiment is conducted a large number of times, the empirical probabilities of the process will converge to the classical probabilities

Subjective DataObtained through surveys and interviews, are considered non-measurable, though marketing research has developed ways to study the intensity of opinions that guide consumer behavior. Subjective data typically include personal perceptions, such as likes, dislikes, attitudes, and opinions.Objective DataObjective data are measurable and typically arise from observation or testing in business areas like sales, operations, manufacturing, and logistics. Data must be valid: that is, the data must accurately represent the true business relationship at hand. Further, the data must be reliable: if we sought to characterize a particular business relationship by gathering data several different times (different samples), the data would reflect the relationship the same way with every sample.Examples of quantitative analysis include...cost-benefit analysis, inventory analysis, logistical analysis, and forecasting revenue.Steps in Quantitative Analysis1. Define problem.

• Develop mathematical model.
• Prepare and input data.
• Find best solution.
• Test solution.
• Analyze results.
• Implement solution.

quantitative analysisEnsuring the use of valid, reliable, and objectively measurable data in order to understand a phenomenon dependent variableA dependent variable is the variable that is being measured, or affected.independent variableindependent variable is free to change in a given model.Fishbone diagramfishbone diagram is sometimes used to determine the cause of a problem.moderating variablemoderating variable is a third variable that changes the established effect of the independent variable on the dependent variable. In a moderating relationship, the relationship between the dependent and independent variables depends on the level of the moderating variable. For example, higher income levels are associated with higher levels of education; however, the effect of this relationship is even stronger for men than for women. Therefore, the strength of the relationship between income and education depends on gender as a third, moderating variable.mediating variableA mediating variable explains the relationship between the dependent and independent variables. Mediating variables are intervening factors that can change the impact of the independent variable on the dependent variable. For example, having a personal trainer helps gym members stick with an exercise routine. The mediating variable might be that the trainer motivates the members, which in turn causes them to stick with their exercise routine. The motivation is the mediating variable and explains why people with personal trainers stick with their exercise routines more than those who do not.