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