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