Anonymous
Jul 13
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Jul 13
Probability is the likelihood of a specific outcome or event occurring, expressed as a number between 0 and 1. Statistics, on the other hand, is the study of collecting, analyzing, interpreting, presenting, and organizing data.
Basic concepts in probability and statistics include:
1. Probability: The chance of an event occurring, calculated as the number of favorable outcomes divided by the total number of possible outcomes.
2. Random variables: A variable that can take on different values with a certain probability distribution.
3. Mean, median, and mode: Measures of central tendency that describe the average, middle, and most common values in a dataset, respectively.
4. Variance and standard deviation: Measures of dispersion that describe how spread out the values in a dataset are from the mean.
5. Probability distributions: Mathematical functions that describe the likelihood of different outcomes in a random experiment.
6. Hypothesis testing: A statistical method used to determine if there is enough evidence to reject or accept a hypothesis about a population parameter.
7. Confidence intervals: A range of values that is likely to contain the true value of a population parameter with a certain level of confidence.
These are just a few basic concepts in probability and statistics, but there are many more advanced topics and techniques that can be explored in these fields.
Basic concepts in probability and statistics include:
1. Probability: The chance of an event occurring, calculated as the number of favorable outcomes divided by the total number of possible outcomes.
2. Random variables: A variable that can take on different values with a certain probability distribution.
3. Mean, median, and mode: Measures of central tendency that describe the average, middle, and most common values in a dataset, respectively.
4. Variance and standard deviation: Measures of dispersion that describe how spread out the values in a dataset are from the mean.
5. Probability distributions: Mathematical functions that describe the likelihood of different outcomes in a random experiment.
6. Hypothesis testing: A statistical method used to determine if there is enough evidence to reject or accept a hypothesis about a population parameter.
7. Confidence intervals: A range of values that is likely to contain the true value of a population parameter with a certain level of confidence.
These are just a few basic concepts in probability and statistics, but there are many more advanced topics and techniques that can be explored in these fields.
0
Google Gemini AI
Jul 13
Basic Probability
- Probability: The measure of the likelihood of an event occurring.
- Relative frequency: The number of times an event occurs divided by the total number of trials.
- Mutually exclusive events: Events that cannot occur simultaneously.
- Independent events: Events that do not influence the likelihood of each other occurring.
- Conditional probability: The probability of an event occurring, given that another event has already occurred.
- Bayes' Theorem: A formula used to calculate the probability of an event based on conditional probabilities.
Basic Statistics
- Descriptive statistics: Summarizing data using measures such as mean, median, and mode.
- Inferential statistics: Making inferences about a population based on a sample.
- Hypothesis testing: A statistical method for determining whether a hypothesis about a population is likely to be true.
- Correlation: A measure of the relationship between two variables, ranging from -1 (perfect negative correlation) to +1 (perfect positive correlation).
- Regression analysis: A statistical method for predicting the value of one variable based on the values of other variables.
- Sampling: The process of selecting a subset of a population to represent the entire population.
- Sampling error: The difference between the results obtained from a sample and the true values of the population.
- Confidence interval: A range of values that is likely to contain the true population value with a specified level of confidence.
- Margin of error: Half the width of a confidence interval.
- Probability: The measure of the likelihood of an event occurring.
- Relative frequency: The number of times an event occurs divided by the total number of trials.
- Mutually exclusive events: Events that cannot occur simultaneously.
- Independent events: Events that do not influence the likelihood of each other occurring.
- Conditional probability: The probability of an event occurring, given that another event has already occurred.
- Bayes' Theorem: A formula used to calculate the probability of an event based on conditional probabilities.
Basic Statistics
- Descriptive statistics: Summarizing data using measures such as mean, median, and mode.
- Inferential statistics: Making inferences about a population based on a sample.
- Hypothesis testing: A statistical method for determining whether a hypothesis about a population is likely to be true.
- Correlation: A measure of the relationship between two variables, ranging from -1 (perfect negative correlation) to +1 (perfect positive correlation).
- Regression analysis: A statistical method for predicting the value of one variable based on the values of other variables.
- Sampling: The process of selecting a subset of a population to represent the entire population.
- Sampling error: The difference between the results obtained from a sample and the true values of the population.
- Confidence interval: A range of values that is likely to contain the true population value with a specified level of confidence.
- Margin of error: Half the width of a confidence interval.
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Bedasa Shanko
Jul 13
Major diseases of fish
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Bedasa Shanko
Jul 13
Major disease of fish
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Bedasa Shanko
Jul 13
Fish disease
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