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Random Sampling and Introduction to Experimental Design

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Simple Random Sample: n measurements from a population Population subset Selected such that: – Every sample of size n from the population has an equal chance of being selected – Every member of the population has an equal chance of being included

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How to select a simple random sample: Assign an number to each child. Use Random Number Table A13 Pick the first 5 two digit numbers. Example

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Simulation: Provides arithmetic imitations of “real” situations. Stock Exchange Problem. Stock Exchange Problem Sampling with replacement: Item selected for a sample is not removed

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Other Sampling Techniques Stratified Sampling: Groups or classes inside a population that share common characteristics (strata). A random sample is drawn for each strata. Systematic Sampling: Elements of a population are in some order, then you select a starting point and every kth element for sampling

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Other Sampling Techniques: Cluster Sampling: A demographic region is divided into sections. Then you randomly select sections or clusters and every member is included in the sampling Convenience Sampling: Results or data that is conveniently and readably obtained

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Introduction to a Statistical Study Basic guidelines for planning a statistical study Identify the individuals or objects of interest Specify the variables as well as protocols for taking measurements or making observations Determine if you will use an entire population (use a census) or a representation sample. If using a sample, decide on a viable sampling method Collect data. Use appropriate descriptive statistics methods (chapters 2, 3, 10) and make decisions using appropriate inferential statistics (chapters 8-12) Note an concerns you might have about your data collection methods and list any recommendations for future studies

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Observation or Experiment? Observational Study: An activity when the experimenter notes differences and their effects on the measurement Experiment: A planned activity that results in measurements. Treatment is deliberately imposed on the individual in order to observe change in the variable.

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Planning and Conducting Experiments Response/Dependent Variable: Variable to be measured in the experiment Explanatory/Independent Variable: Variable that may explain the differences in responses Control: Used to establish the baseline response expected if no treatment is given

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Planning and Conducting Experiments Placebo: A control group for some medical experiments Looks exactly like the real medicine Randomized two-treatment experiment: Patients assigned to the treatment and control group by random selection

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Planning and Conducting Experiments Single-Blind: Either the patient does not know which treatment he/she is receiving or the person measuring the patient’s reaction does not know Double-Blind: Both the patient and the person measuring do not know which treatment the patient was given

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Survey Nonresponse: Selected respondents refuse to respond Too many nonresponses can cause the study to be biased Voluntary Response: Often over represents people with strong opinions Hidden Bias: The way you conduct the survey many leave part of a population out

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Results Lurking/Confounding Variable: The effect of one variable on another can be hidden by other variables for which no data has been obtained Generalizing results: Replication

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