Python Basics and Biostatistics

SUMMARY

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TITLE STATISTICS TOPICS PYTHON TOPICS
Introduction
  • Associate common terms with statistics.
  • Explain in general terms how statistics can be useful.
  • Write and execute a simple PYTHON script.
  • Use the print statement.
  • Identify and use the newline character.
  • Locate and write the bang line in a PYTHON script.
    • Numeric Variables
  • Calculate the arithmetic mean
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  • Store values in variables
  • Use the four basic arithmetic operators in a PYTHON script
  • Name and identify scalar variables
    • Simple Comparisons
  • Undertand the importance of comparison in science
  • Use the greater than and less than operators to perform simple comparisons
  • Write comments in a PYTHON script
  • Differentiate between the bang line and a comment line
    • Variability and Range
  • Find the range of a group of numbers
  • Create and populate arrays
  • Use the foreach loop
  • Use the comma operator
    • Finding the Median Value
  • Find the median of a data set
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  • Use the sort function
  • Implement numeric or alphabetic sorting
  • Use an if/else construct
  • Use the modulus operator
  • Use array indexes
    • Tallying Results
  • Using a tally to keep track of data points
  • Implement a never ending loop
  • End a loop at any point within it's execution
  • Use the tab symbol
  • Use the chop function
  • Increment a scalar
  • Add values to a list
    • Quartiles
  • Read a box-and-whiskers graph
  • Divide data points into quartiles
  • Construct and populate associative arrays
  • Use the .. operator
  • Use the logical and operator in an if statement
  • Set and turn off flags
  • Get a list of keys from a hash
    • Deviation From the Mean
  • Calculate average deviation from the mean
  • Input values from standard input
  • Use the abs function
  • Use the chomp function
  • Compare non-numeric values
    • Variance and Standard Deviation
  • Calculate population variance and standard deviation
  • Calculate sample variance and standard deviation
  • Use sqrt function
  • Use my variables
  • Import the strict module
    • The Gaussian Distribution
  • Calculate the z for an individual score
  • Recognize the Gaussian distribution
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  • Recognize Python built in functions
    • The Prediction Interval
  • Calculate the prediction interval
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  • Store and retrieve values from a hash
  • Lookup values stored in a hash
    • Confidence Interval of the Mean
  • Interpolate between two values
  • Calculate the 95% CI for a data set
  • Use the shift function
    • Conversion Between SEM and SD
  • Convert SEM to SD
  • Calculate the t distribution
  • Use an if/else construct
  • Write a dual function script
    • False Positives
  • Understand what is meant by the term false positive
  • Work with the logical OR and logical AND operators
  • Use the ** operator to raise a base by a power
    • CI of the Difference Between Means
  • Calculate the 95% CI for the difference between means
    		•
  • Coordinate the use of values stored in arrays with if/elsif/else constructs
    • Paired Groups
  • Calculate the 95% CI of the difference between means for paired groups
  • Use array slicing to manipulate values in an array
  • Use the range operator in the context of an array
    • Relative Risk
  • Calculate the 95% CI of the logarithm of the relative risk
  • Calculate the antilog of a number
  • Use the Python log function
    • Probability vs. Odds
  • Explain the difference between probability and odds
  • Convert from odds to probability and vice versa
  • Calculate the odds ratio
  • Use split to convert a scalar into an array
  • Sort odd and even numbers using the modulus operator
    • Random Sampling
  • Explain the statistical reliability of random sampling
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  • Redirect script output to a file
  • Push scalar values onto a list
  • Generate random numbers
    • Sensitivity and Specificity
  • Calculate sensitivity and specificity
  • Create subroutines in Python
    • Positive and Negative Predictive Values
  • Calculate positive and negative predictive values
  • Fill out a result matrix based on values for prevalence, specificity, and sensitivity
  • Pass values to subroutines
    • Bayes' Theorem
  • Convert odds to probability and vice versa
  • Calculate post-test odds
  • Use nested and recursive subroutines
    • Correlation Coefficient
  • Calculate the correlation coefficient
  • Use for loops
    • Slope and Intercept
  • Calculate the slope of the best-fit line given a set of data points
  • Calculate the y-intercept of the best-fit line
  • Use redo, last, and next to modify loop behavior
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