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What does it consist of?
- Collection, Classification
- Description, Analysis
- Interpretation, Presentation
Stats (Types & Usage)
- Descriptive & Analytical- summary measures of data
- -Scientific method for interpreting data obtained
- Vital Stats (PH agencies)- Birth, deaths, marriage, health related conditions
- -Re-enforcement of other findings
- -Statistical reasoning (clinical judgment, scientific judgment)
Refer to individual values (3things)
Properties (4 things)
- Individual values: 1. presented 2.measured 3. observed
- Properties: 1. sample population 2. grouped or ungrouped
- 3. quantitative or qualitative 4. discrete or continuous
Where do we get Data?
Types of Sample population?
- - from a population
- -Types of sample populations :(simple random, non-random, Stratified selected)
What is grouped? Ungrouped?
- Groups= consist of identical data, by frequency
- Ungroup= Presented individually(even if identical)
- Quantitative( base on Number)
- Qualitative (non-numerical, based on categories)
- Discrete (distinct categories, limited # of possible values exist)
- Continuous (Unlimited # of possible values)
- a. exactness, measure true value of what being studied
- b. consisten and reproducible
- c. stable, dependable, sound
- d. measure what is supposed to measure
a. complete summary of frequenies or proportion of a characteristic for a series of data from a population or sample.
b. AKA: Gaussian (continuous bell shape)
c. (+) skewed= to the right, (-) skewed= to left
Descriptive stats (Measure of central Affinity)
1. Arithmetic Mean?
- 1. Mean (sensitive to extreme values in a series)
- - Add all #/ Total #'s in series
- 2. Divides series into 2 equal groups (not sensitive to extreme values), better representative of central tendency than mean.
- - also it is the middle of Percentiles= Values divide series into defined percentages (level of measurment below which a specified portion of distribution falls)
- - Middle number
- 3. if ODD # of values (lowest--> highest and divide in 1/2)
- - if EVEN # (2 values divide in 1/2, calcutae their mean)
4. Most occuring values in a series (Epi studies for peak of disease occurance)
5. Difference b/w highest and lowest value (measure data spread)
- 6. Main use to calculate standard deviation
- -SD= +ve sq. root of the variance
8. Rule of probability?
9. Null hypothesis
- 7. quant. expression of likelihood of occurrence
- - defined in terms of relative frequency (never >1 or <0)
- 8. PR (A does not occur)= 1- PR (A occurs)
- -PR (A/B)= # of times A&B occur jointly or of times B occurs
- 9. Samples compared are similar (any difference is due to chance)
- - used to define significant difference
- - testing or examining individual or large groups of people
- -It separates from those who have high probability of having condition under study.
1. Theories concerned w/ diseases, diagnostic testing, used as a case finding tool, and treatment testing.
- 2. Programs (must meet certian criteria)
- -Segment being screened @ relatively high risk for cond.
- -the disease= of enough concern to community being screened
- -Un-diagnosed disease= should be more responsive to TX than if diagnosed @ later symptomatic stage
- (screening test are: sensitive/specific, applicable to Lg #, easy and quick, should not cause harm, inexpensive)
- (Those with (+) results guaranteed follow up evaluation)
- 3. ability to ID correctly those who do NOT HAVE the disease (if 100% sensitivity= (-))
- -ability of the test to give a (+) result when person tested truly has disease.
- - Is a %
- 4. ability to ID correctly those who have the disease (if 100%= (+))
- -ability to test to give a (-) result when person tested is free of disease
- -Is a %
Setting Cut-off? depends on?
- -Natural Hx of disease
- -effectiveness of intervention (early or late)
- -if disease is rare: Sensitivity=high (or cases present will be missed)
- -If very lethal (early detection improves prognosis)
- (high sensitivity is necessary)(false + are tolerated, false -'s are not)
Screening if very rewarding (high sensitivity)