Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

Quality Engineer > 6. Quantitative Methods and Tools > Flashcards

6. Quantitative Methods and Tools Flashcards

1
Q

Type of data - example (1, 2, 3, 4)

A

Discrete Data (Attributes)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Type of data - example (1.25, 5.49, 3.12)

A

Continuous Data (Variables)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Nominal

A

Can only count items

Indicates characteristic by name, category, number, presence/absence

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Ordinal

A

Order is important

Grouping into categories having an attribute

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Fixed or defined scale but no true zero

Potential zero point

A

Interval

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

There is a true zero

Can add, subtract, multiply and divide values

A

Ratio

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Range, standard deviation, and variation describe..

A

Dispersion

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Distribution of sample averages will tend toward a normal distribution as the sample size (n) increases. Thus, the sampling distribution of the mean will follow a normal distribution with a certain mean and standard deviation.

A

Central Limit Theorem

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q
  • Shows the pattern of variability around the center.
  • Organizes information for ease in calculating the statistics, such as the sample mean and the sample standard deviation.
  • The number of classes should be at about the square root of the sample size
A

Frequency Distributions

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

A type of histogram, 1st digit, 2nd digit…

A

Stem-and-Leaf Plots

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Use five key data points to graphically compare data produced from different sources (different machines, operators, etc)

A

Box-and-Whisker Plots

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Probability Plots are used to…

A

Used to determine the type of distribution from which a set of data may have come

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

The _______ of any single observation, xi, is the mean of the population, μ , from which the observation has come. The notation is given as E(xi) = μ

A

Expected Value

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q
  1. Making a hypothesis of what we expect to find
  2. Collecting data
  3. Analyzing the data
  4. Drawing a conclusion about the validity of the hypothesis
A

Analytical Studies

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Type of distribution where:

Most of the data points are concentrated around the average (bell shaped curve)

A

Normal Distribution

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Type of distribution where:

Equal probability of outcomes

A

Uniform Distribution

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

Type of distribution where:

Variables are distributed jointly

A

Bivariate Normal Distribution

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

Which type of distribution:
Analyzes reliability. Similar to Poisson, is used to determine the average time between failures or average time between a number of occurrences
Examples - time between events, time to

A

Exponential Distribution

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

Which type of distribution:
Skewed-right with most data in the left tail, and consisting of the distribution of the random variable whose natural logarithm follows the normal distribution

Examples - response time, time-to-failure data, and time-to-repair data

A

Lognormal Distribution

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

Which type of distribution:
• β is the shape parameter – defines the probability distribution function
• θ is the scale parameter – describes the magnitude of the x-axis
• Both are greater than zero

A

Weibull Distribution – analyzed reliability.
Similar to lognormal

Examples - time to fail, time to repair, and material strength

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

Which type of distribution:
Used when testing a population variance against a known or assumed value of the population variance. It is skewed to the right (i.e., it has a long tail toward the large values of the distribution)

• Formed by summing the squares of the standard normal random values

A

Chi Square Distribution

22
Q

Which type of distribution:
Used to determine the confidence interval of the population mean and confidence statistics when comparing the means of sample populations. The shape and area of the distribution approaches that of the normal distribution as the sample size increases.

A

Student’s T Distribution

23
Q

Which type of distribution:
When parameter being measured takes on only certain values

Examples- integers

A

Discrete Distribution

24
Q

Which type of distribution:
Used to estimate the number of instances a condition of interest occurs in a process or population. When the condition may occur multiple times in one sample unit and you are interested in knowing the number of individual characteristics found

A

Poisson Distribution

25
Q

Which type of distribution:
When items are drawn from a population without replacement. Similar in nature to the binomial distribution, except the sample size is large compared to the population. Appropriate whenever the sample size is greater than 10% of the population

A

Hypergeometric Distribution

26
Q

Status if the difference between the sample and the population caused by the sampling method

A

Bias

27
Q

Status if the average of all possible values is equal to the parameter being estimated

A

Unbiased

28
Q

The standard deviation of a sample statistic or estimator indicating the amount of error that will occur when a sample mean is used to estimate the mean of a population

A

Standard Error

29
Q

The stated coverage for a fixed proportion of the population with a declared confidence

A

Tolerance Interval

30
Q

Change, or improvement, and one that could have occurred by chance magnitude of difference or change required to distinguish between a true difference, change, or improvement, and one that could have occurred by chance

A

Statistical Significance

31
Q

The amount of difference, change, or improvement that will add practical, economic, or technical value to an organization. Often this is a constraint on the process flow.

A

Practical Significance

32
Q

Comparing data sets by determining if the means are equal

A

Paired-Comparison Tests

33
Q

Comparing an observed (O) frequency distribution to an expected (E) frequency distribution

A

Goodness-of-fit Tests

34
Q

Determine if there are statistically significant differences among group means by analyzing group variances. Evaluates the importance of several factors of a set of data by subdividing the variation into component parts

A

Analysis of Variance (ANOVA)

35
Q

Used to analyze data via a two-way classification involving two factors with data that are usually attribute in nature such as frequency or counts. This tool is used to test whether two sources of variation are statistically independent. The test statistic used is the Chi-square statistic (χ2).

A

Contingency Tables

36
Q

(Shewhart) philosophy focusing on optimizing continuous improvement by using statistical tools for analyzing data, making inferences about process behavior, and then making a decision

A

Statistical Process Control (SPC)

37
Q

In Regression Analysis, vertical distance between observed y and calculated y is used to calculate _____

A

Standard error of the estimate

38
Q

If two variables have a linear correlation coefficient of -.97 , as one variable _____, the other ______

A

increases, decreases

39
Q

______ helps reduce the effect of uncontrolled variables in an experiment

A

Randomization

40
Q

______ can most cost-effectively detect and eliminate many software errors in a quality information system

A

Design Review and Code Inspections

41
Q

______ is useful when data is in subgroups and time-ordered

A

X and R Chart

42
Q

Type 2 error risk

A

Not rejecting the null hypothesis when it is false

43
Q

A test for significance in an analysis of a variance table

A

F-Test

44
Q

Removing larger number to view just decimal values

A

Data Coding

45
Q

Chart:

Plotting data over time

A

Run Chart

46
Q

Distribution most similar to normal distribution

A

Students T Distribution

47
Q

Chart:

Variability from one individual value to another

A

Moving Range Chart

48
Q

Benefit of using fraction factorial design instead of full factorial design

A

Reduces costs

49
Q

Distribution of rolling dice

A

Uniform Distribution

50
Q

Takes centering of the process into account

A

Ppk

51
Q

If Cp = 1, the process variation is…

A

Equal to the specification width

52
Q

The square of the correlation coefficient

A

Coefficient of Determination

Quality Engineer (16 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions