SCMA 350 Exam 1

use of data and information to gain insight and knowledge and aid business decision maker

summing up all variable values/number of entries

use instead of mean when extreme values exist

most frequently observed value

at least “p” percent of the observations are less than or equal to the value of the “pth” percentile and (100-p)% > to this value

1st, 2nd, 3rd quartile: 25th, 50th, and 75th percentile

difference between maximum and minimum values observed

middle 50% of the data = Q3-Q1

can show average, median, and quartiles, constant line: very helpful when distinguishing between categories comparing using target value (numerical)

measure of how much two random variables change together, indicates positive or negative direction

relative to extreme values among observations

most values smaller and extreme values skew right (goes downward)

most values higher and extreme values skew left (going upward)

we use this to represent the shape of distribution

we use this to represent variability

can display all of the numerical measures described above: quartiles, standard deviation, covariance

we can use different segmentation and comparison across the category to examine relationships: days of week, quality ratings, segments of business

displays the relationship between two variables in a table: frequency, proportions/marginals, comparisons using numerical variable, visualizations

unique way (similar to pie chart) to display crosstabulation across multiple categories

service or product characteristics that can be measured, such as weight, length, volume, or time

service or product characteristics that can be quickly counted for acceptable performance

larger sample sizes tend to __________ ___________

are random, unidentifiable sources of variation that are unavoidable with the current process

any variation causing factors that we can identify and eliminate

a process is in _________ ___________ when the location, spread, or shape of its distribution does not change over time

monitors process variability

checks the process output to determine: on average, consistent with target variable, current performance, consistent with past performance

a chart used for controlling the proportion of defective services or products generated by the process

a chart used for controlling the number of defects when more than one defect can be present in a service or product

finding the defendent guilty based on evidence

we do not find enough evidence to find the defendant guilty

the smaller, the stronger evidence against the null hypothesis

comparing two subgroups where variance of both subgroups is known

comparing two subgroups where variance of subgroups is unknown

comparing three or more subgroups

assumptions of anova include

comparing three or more subgroups