SCMA 350 Exam 1

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37 Terms

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business analytics

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

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mean

summing up all variable values/number of entries

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median

use instead of mean when extreme values exist

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mode

most frequently observed value

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percentile

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

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quartiles

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

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range

difference between maximum and minimum values observed

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interquartile range

middle 50% of the data = Q3-Q1

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reference lines

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

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covariance

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

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skewness

relative to extreme values among observations

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positive skew

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

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negative skew

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

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histogram

we use this to represent the shape of distribution

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box and whisker plot

we use this to represent variability

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numerical variables

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

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categorical variables

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

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crosstabulation

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

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stacked bar chart

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

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variables

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

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attributes

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

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decrease variation

larger sample sizes tend to _

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common causes

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

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assignable causes

any variation causing factors that we can identify and eliminate

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statistical control

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

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r chart

monitors process variability

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x chart

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

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p-chart

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

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c-chart

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

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alternative hypothesis

finding the defendent guilty based on evidence

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null hypothesis

we do not find enough evidence to find the defendant guilty

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p-value

the smaller, the stronger evidence against the null hypothesis

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z-test

comparing two subgroups where variance of both subgroups is known

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t-test

comparing two subgroups where variance of subgroups is unknown

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ANOVA

comparing three or more subgroups

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normal distribution (try ln if not), equal variances (levene’s test)

assumptions of anova include

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kruskal-wallis test

comparing three or more subgroups