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Probability is essential in inferential statistics because it quantifies the ______ in drawing conclusions about a population from a sample.
uncertainty
Probability enables us to estimate the likelihood of various ______ and make informed decisions.
outcomes
Collection of the data is the first step in conducting statistical ______.
inquiry
Data can be classified as primary or ______.
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In engineering, the three basic methods of collecting data are through retrospective study, observational study and through a ______ experiment.
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A systematic method of collecting and measuring data helps to provide answers to relevant ______.
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Both probability and statistical inference are vital for making ______ decisions.
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Methods of data collection help in measuring data from different sources of ______.
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Certain data can be classified as either qualitative or ______ data.
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Ungrouped (or raw) data are simply the collection of data as they are ______.
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A ______ is a measure of a characteristic of a sample.
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A constant is a characteristic or property of a population or sample which is ______ to all members of the group.
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Data are facts, figures, and information collected on some characteristics of a ______.
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All trademarks, images and symbols belong to their respective ______.
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Observational and Experimental are forms of ______ analysis.
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Usage of any image requires prior notification and ______.
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In convenience sampling, people are selected based on their accessibility and __________.
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Quota sampling aims to achieve a spread across the target population by specifying who should be recruited according to certain __________.
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In purposive sampling, participants are chosen based on their knowledge and understanding of the __________ question.
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Snowball sampling involves participants inviting __________ they know to take part in the research.
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Determining what type of sampling to use starts with defining your research __________.
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Assessing the nature of your population is crucial when selecting a __________ method.
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In convenience sampling, the sample is gathered from a __________ location.
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In snowball sampling, one participant leads to another, creating a __________ of recruitment.
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The mean is influenced considerably by the presence of the extreme ______.
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The ______ places emphasis on the true 'center' of the data set.
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The sample mean is the ______ of the data in a sample.
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The mode represents the most frequent ______ in a distribution.
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Standard deviation is a measure of the ______ of data points in a dataset.
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Standard deviation indicates how much the values typically differ from the ______.
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A rarely used measure of central tendency is the ______.
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The mean, median, and ______ are all measures of central tendency.
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Variance is a statistical measure that represents the average of the squared differences between each data point and the ______.
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Design of Experiments, or DOE, is a tool to develop an experimentation strategy that maximizes learning using minimum ______.
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Screening experiments are used to identify the important ______ that affect the process under investigation.
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The objectives of optimization may be to either increase yield or decrease ______.
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The identification of the objectives of conducting the experiment is part of the ______ phase.
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Variance indicates the spread of data in a ______.
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Optimization can help to find settings that achieve both increased yield and decreased ______ at the same time.
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The assessment of time and available resources to achieve the objectives is a crucial part of the planning ______.
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Study Notes
Probability and Statistical Inference
- Probability is crucial for making informed decisions in statistical inference.
- It quantifies the uncertainty in drawing conclusions about a population based on a sample.
- Probability allows us to estimate the likelihood of various outcomes.
Methods of Data Collection
- The first step in statistical inquiry is data collection.
- Data collection involves gathering and measuring information systematically.
- Data can be primary or secondary.
Data Collection Methods in Engineering
- Three methods of data collection are used in engineering: retrospective studies, observational studies, and designed experiments.
Data Definitions
- Data refers to facts, figures, and information collected on characteristics of a population or sample.
- Qualitative data is descriptive and non-numerical.
- Quantitative data is numerical and can be measured.
- Ungrouped (or raw) data is data that is not organized in any specific way.
- A constant is a characteristic or property of a population or sample that is common to all members of the group.
- Statistics measures a characteristic of a sample.
Non-Probability Sampling Methods
- Convenience Sampling selects participants based on their accessibility and availability.
- Quota Sampling aims to represent the target population through specific groups or criteria.
- Purposive Sampling carefully selects participants based on knowledge and understanding of the research question.
- Snowball or Referral Sampling uses participants to recruit new participants through their networks of friends and family.
What Type of Sampling Should I Use?
- Factors to consider:
- Define your research goals.
- Assess the nature of your population.
Measures of Central Tendency
- The Mean is the average of all values in a dataset.
- The Median is the middle value in a sorted dataset.
- The Mode is the most frequent value in a dataset.
Measures of Variability
- Standard Deviation measures the dispersion of data points around the mean, indicating how much values typically differ from the mean.
- Variance represents the average of squared differences between each data point and the mean, indicating the spread of data in a dataset.
Introduction to Design of Experiments
- Design of Experiments (DOE) is a tool for maximizing learning with minimal resources during experimentation.
Planning a Design of Experiments
- The planning phase focuses on identifying the objectives of the experiment, assessing time requirements, and considering available resources to achieve the objectives.
Screening Experiments
- Screening experiments are used to identify significant factors affecting a process from a large pool of potential factors.
Optimization Experiments
- Optimization experiments aim to either increase yield, decrease variability, or achieve both simultaneously, depending on the product or process under investigation.
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Description
This quiz covers fundamental concepts in probability and statistical inference. It explores various methods of data collection relevant to engineering and differentiates between types of data. Test your understanding of these essential topics in statistics.
