Undergraduate, Post-graduate, Medical Researcher.
| Sr No | Concepts | Description |
|---|---|---|
| 1 | Data | Collection of Information is Known as Data |
| 2 | Qualitative Data | When data classified on basis of quality is known as qualitative data. Ex: Gender of patient. |
| 3 | Quantitative Data | When data classified on basis of quantity is known as Quantitative data. Ex: Age of patient. |
| 4 | Nominal Data | When data classifies into names, labels or categories in which no order or ranking can be imposed. Ex: The blood group of patients i.e A, B, AB & O |
| 5 | Ordinal Data | When data classifies data into categories that can be ordered or ranked. Ex: Socio-economic class of patient i.e lower, middle & Upper. |
| 6 | Interval Data | When Ranks data, precise differences between units of measure exist, but there is no meaningful zero. Ex: IQ scores of students |
| 7 | Ratio Data | It has all the characteristics of the interval level, but a true zero exists. Also, true ratios exist when the same variable is measured on two different members of the population. Ex: It makes sense to say that a 70 kg adult weighs twice as much as a 35 kg child. |
| 8 | Master Table | Main table in all, Summarization of Research. It includes lot of Rows & Columns. |
| 9 | Arithmetic Mean | The ratio of sum of all observation to the number of observation is known as Arithmetic Mean. |
| 10 | Standard deviation | The standard deviation is square root of the average square of deviation from mean. Useful for measurement of variation. |
| 11 | Null Hypothesis [H0] | A neutral statement about population parameter is known as Null Hypothesis |
| 12 | Alternative Hypothesis [H1] | The opposite or complimentary statement of Null Hypothesis is known as Alternative Hypothesis. |
| 13 | P-value | The probability that an observed difference could have occurred by chance. • If P < alpha (0.05), the difference is statistically significant. • If P > alpha, the difference between groups is not statistically significant. |
| 14 | t-test [Student’s t-test] | t-test is useful for quantitative data. When data is normally distributed & sample size less than equal to 30. |
| 15 | Paired t-test | The paired t-test is used to check significant difference pre treatment and post treatment. Same individual is observed twice. |
| 16 | Unpaired t-test | The unpaired t-test is essentially used to find significant difference of the two sample means. |
| 17 | Chi-Square Test | The chi-square test is useful for Qualitative data & to check association between two attributes. |
| 18 | F-test [Fisher’s F-test] | F-test is useful for checking variability between two sample groups. When data is Quantitative and normally distributed. |
| 19 | Z-test | Checking mean difference between two sample groups. When Data is normally distributed and large Sample size (≥30). |
| 20 | Correlation | Relationship between two variables is known as correlation. |
