Biostatistics test 1
Experimental study
Apply some treatment and then observe it's effect on the subject
Law of large numbers
As a procedure is repeated again and again, the relative frequency probability from rule number one of anything tents to approach the actual probability
Qualitative data
Can be separated into different categories that are distinguished by non-numeric characteristics
Quantitative data
Consists of numbers representing counts or measurement
What are the two types of quantitative data?
Continuous and discrete
What are the probability terms?
Disjoint, independent, dependent, complement, event, sample space, mutually exclusive
Bimodel
Distribution is a continuous probability distribution with two different modes.
Multi model
Distribution is a probability distribution with more than one P, or mode. And distribution with one peak is called unimodal. And distribution with two peaks it's called Bimodel. A distribution with two peaks or more is multimodal
Complement
Event a, denoted by a consists of outcomes in which event he does not occur
Disjoint or mutually exclusive
Events A and b cannot occur at the same time
Example of qualitative data
Gender ( male/female) of bears
Discrete random variable
Has either a finite number of values or accountable number of values, were countable refers to the fact that there might be infinitely many values, but they can be associated with a counting process
Continuous random variable
Has infinitely many values, and those values can be associated with measurements on it continue skilled without gaps or interruptions
Examples of data
Height, weight, exercise habits, health behaviors
Dependent
If A and B are not independent
The rare event rule for inferential statistics
If Under a given assumption, the probability of a particular observed event is extremely small, we conclude that the assumption is probably not correct
Independent
If the occurrence of one does not affect the probability of the occurrence of the other. Example several events are similarly independent if the occurrences of any does not affect the probabilities of the occurrence of others
Ordinal level of measurement
If they can be arranged in some order, but differences between data values are there cannot be determined or are meaningless - categories with some order
Continuous data
Infinitely many possible values on a continuous scale without gaps or jumps
What is the difference between an observational study and an experimental study?
Investigators observe subjects and measure variables of interest without assigning treatments to the subjects while the other study have the treatment that each subject receipts is determined beyond the control of the investigator.
Histogram
Is a paragraph in which the horizontal scale represents classes of data values and the vertical scale represent frequencies. The height of the far correspond to the frequency values, and the bars are drawn adjacent to each other without gaps
Sample
Is a sub collection of members selected from part of a population
Nominal level of measurement
Is characterized by data that consist of names, labels, or categories only. The data cannot be arranged in an ordering scheme such as (low to high) -categories only
Interval level of measurement
Is like the ordinal level, with the additional property that the difference between any two data values is meaningful. However, data at this level do not have a natural zero starting point (we're not know if the quantity Is present) - differences but no natural starting point
Census
Is the collection of data from every member of the population
Population
Is the complete collection of all elements (scores, people, measurements, and so on) to be studied. -The collection is complete in the sense that it includes all subjects to be studied
Ration level of measurement
Is the interval level with the additional property that there is also a natural zero starting points were zero indicates that none of the quantity is present. For values at this level, differences and ratios are both meaningful - Differences and a natural starting point
Statistic
Is the measurement describing some characteristic of a sample
Example of continuous data
PH of a sample, patient cholesterol levels The amount of milk from cows are continuous data because they are measurements that can assume any value over a continuous span.
Descriptive statistics
Summarizes the population that up by describing what was it serve in a sample numerically/graphically
If the skewness is on the middle of the histogram what does it mean?
Symmetrically distribution histogram
Inferential statistics
Testing hypothesis/drawing conclusions
What a probability of 1 means?
The event it always happens
Median
The middle value if n is an odd number or midway between the two middle values I'd n is an even number
Conditional probability's
The probability of an event a, given that another event B has already occurred
Mean
X values Sample arithmetic mean
Examples of ordinal level of measurement
- Course grades: A college professor of science grades of A, B, C, D, or F - Ranks: based on several criteria, biologist rings all bears and one region according to their aggressiveness
Examples of inferential statistics
- Do people who smoke have more lung cancer than those who don't? - Are women in LA County on average heavier than the average woman in the United States?
Parameter
- Is the measurement describing some characteristic of a population -they are usually unknown and we wish to make statistical inferences about parameters
Cluster sampling
- Refers divide the population area into sections or clusters, the randomly select some of those clusters, and then choose all the members from those selected clusters - Divide the population into sections are clusters, randomly select of those clusters; choose all members from selected clusters
Examples of interval level of measurement
- Temperatures: body temperatures of 98.2 Fahrenheit and 96.6 F - Years of cicada emergence: The years 1936, 1953, 1970, 1987, and 2004 Time did not begin in the year zero, so the year zero is arbitrary can stead of being a natural zero starting point representing "no time"
Biostatistics application
- The application of statistic to a wide range of topics in biology. - The science of biostatistics income passes - the design of biological experiment, the collection, summarization, and analysis of data from those experiment -The interpretation of, and the inference from the results
Systematic sampling
- We are randomly select a starting point and then select every kth ( such as every fifth element in the population) - Select some starting point and then select every kth element in the populations
Convenience sampling
- We simply collect results that are easy (convenient to get) - use results that are readily available
Stratified sampling
- We subdivide the population into at least two different subgroups or Strata that share the same characteristics such as gender or age bracket, the draw sample from each subgroup or stratum - Subdivide the population into so proof that share the same characteristics, then draw a sample from each stratum
Outlier
- an observation which does not appear to belong with the other data - can arise because of a measurement or recording error or because of equipment failure during an experiment, etc. - Might be indicative of a subpopulation example and normally low or high value in a medical test could indicate presence of an illness in the patient
Frequency distribution
- for a continuous variable presents the counts of observations grouped within pre-specified classes or groups - list data values either individually or by groups of intervals, along with their corresponding frequencies or counts
Examples of descriptive statistics
- the average mean weight of United States women age 21 to 65 - The number of people living in LA County and the proportion in ethnic group - Smoking status; never a smoker, former smoker, current smoker
What is the difference between descriptive statistics and inferential statistics?
- uses the data to provide descriptions of the population, either through numerical calculations or tables while the other statistics make inferences and predictions about a population based on a sample of data taken from the population in question
Random sample
-Members from the population are selected in such a way that each individual member has the same chance of being selected -members of the population are selected in such a way that each has an equal chance of being selected
Simple random sample
-Size n subject is selected in such a way that every possible sample of the same size n has the same chance of being chosen -Selection so that each has an equal chance of being selected
Examples of nominal level of measurement
-Survey responses of yes, no an undecided -The colors of peapods green and yellow is used in a genetics
Statistics
A collection of methods for; planning experiments, obtaining data, and then organizing, summarizing, analyzing, and temperature young, presenting, and drink conclusion based on the data subset of the population
Skewness
Left, right, symmetric
What a probability of zero means?
Means the event never happens
Skewness
Measures the degree of a symmetry exhibited by the data
Mode
Most frequent no. Is the most commonly occurring value
If the skewness is on the right-hand side of the histogram what does it mean?
Negatively skewed histogram - There are small number of low observations and a large number of high ones - When the median is greater than the mean
What are the continuous data levels of measurement?
Nominal, ordinal, interval, ratio
Example of discrete data
Number of bacteria colonies in a culture The numbers of eggs that hens are discrete data because they represent counts
Observational study
Oberserving and measuring specific characteristics without attempting to modify the subject being studied
Data
Observations such as measurements, survey, responses that have been collected
Multiplication rule of probability
P (A and B) = P( event A occurs in a first trial and event B occurs in a second trial) P (A and B) = P (A) * P(B|A)
Addition rule of probability
P (a or B) = P in a single trial, event a occurs or event b occurs or they both occur P (A or B) = P (A) + P(B) - P(A and B)
Discrete data
When the number of possible values is either finite or countable
If the skewness is on the left histogram what does it mean?
Positively skewed histogram -there are more of survey shins below their means and above it - when the mean is greater than the median
What are the sampling methods?
Random, simple random sample, cluster, convenience, stratified, systematic
Standard deviation
S is the square-root of the variance S has the advantage of being the same units as the original variable x
Variance
S2 is the arithmetic mean of the squares deviations from the sample mean
Range rule of thumb
Simple range is the difference between the largest and the smallest observations in the sample Sensitive to extreme values
What are the boundaries of probabilities between 0 and 1 inclusive
Total probability of all possible events always sums up to one
Example of quantitative data
Weight
Examples of ratio level of measurement
Weights: Weight in kilograms of bold eagles zero KG does represent no wait and four KG is twice as heavy as to KG Aegis : ages and days of bald eagles zero does not represent a newborn with no aging, and an age of 60 days is three times as old as an age of 20 days
Biostatistics Dictionary
the science of statistics applied to the analysis of biological or medical data