Lecture 1

SCI3031 SEF.

The average of squared deviations from the mean.

Range, variance, and standard deviation.

To assess whether the populations they come from differ from each other.

Probability in Biological and Environmental Contexts.

To summarize or describe the characteristics of a data set.

Standard Error measures variability across samples, while Standard Deviation measures variability within a single sample.

Measures of central tendency, measures of variability, and frequency distribution.

ddeng@hkmu.edu.hk.

Parameters refer to populations, while statistics refer to samples.

The level of measurement and distribution.

A summary that includes the lowest value, Q1 (25th percentile), Q2 (median), Q3 (75th percentile), and the highest value (Q4).

2 hours.

Annual reports, various censuses, distribution surveys, museum records, and social media statistics.

It is impossible to imagine life without some form of statistical information being readily at hand.

The number of times a particular value or category occurs in a dataset.

Statistics is part of the life of every serious biologist.

Because these tests are sensitive to variance.

Average species population sizes, average temperatures, average levels of a particular pollutant, etc.

It indicates that a specific value or category appears 22 times in the dataset.

No, there is no best measure; using only one is considered the worst.

Statistical information is present around us in various forms.

The variability or spread of data.

It helps you grasp the likelihood of unusual events.

Variability across multiple samples of a population.

Go to Analyze > Descriptive Statistics > Frequencies.

Introduction to Biostatistics.

Nominal, Ordinal, and Scale.

A science that deals with methods of collection, organization, analysis, interpretation, and presentation of numerical information.

Necessary tools and conceptual foundations in quantitative reasoning.

The average amount of variability.

Median growth rate of a plant species or median level of rainfall in a particular location over time.

The median is the middle value, indicating that A is greater than B.

Interquartile Range.

It is definitely the worst approach.

Age and income.

Identifying Statistical Significance of Scientific Research.

Ordinal.

Variability is everywhere.

The center of the data set (mean, median, mode).

No, parameters are fixed values for a given population.

The middle value in a data set when the numbers are arranged in order.

SPSS.

It helps in assessing the reliability and consistency of data.

20%.

For reliable statistical analysis.

Analyzing and interpreting real-world data using statistical software and critically evaluating data to support or refute scientific hypotheses.

Introduction, exploration and interpretation of data, use of statistical software, and critical evaluation of findings.

Bars can be arranged in any order and represent distinct categories.

By using statistical analysis to identify and quantify environmental health issues.

They provide a fuller picture of the data, indicating how spread out it is.

It represents the average of a sample statistic, such as average annual rainfall based on yearly data.

Critical information about the data set.

To evaluate the credibility and usefulness of information.

The extent to which data points in a dataset differ from each other.

Data Analysis Techniques in Biological and Environmental Case Studies.

X5920.

2 hours of lecture and 1 hour of tutorial.

A dataset with a wide range of values, such as test scores of 50, 70, 90, and 100.

The occurrence of data within the data set (count).

Data using measures of central tendency (mean, median, mode) and measures of variability (range, interquartile range, standard deviation).

Central tendency provides a snapshot of data characteristics, while variability gives insights into consistency and diversity.

The 75th percentile.

Data sets that include measurements like weight, height, temperature, and height of plants.

Data sets that involve two variables, such as percentage score and age of students in a class.

As the average, which is the sum divided by count.

6, as it occurs most often.

Biostatistical Analysis.

Problems in interpretation and decision-making.

Collection, organization, analysis, interpretation, and presentation of information.

How far a score lies from the mean.

It tells you, on average, how far each score lies from the mean.

Collection, processing, analysis, interpretation, and presentation of data.

In a left-skewed distribution, the tail extends to the left.

A number describing a whole population (e.g., population mean).

12 sessions.

Spread, scatter, or dispersion.

Lecture on Topic 3 and Exercise 1.

The median.

Parameters describe entire populations; statistics describe samples.

Basic statistical analysis techniques using statistical software.

4 hours.

A score higher than 85.

The observation that a tall person is generally considered to be heavier than a short person.

It provides data-driven insights to inform policies and practices for environmental health.

Variability within a single sample.

The most commonly observed species in a habitat or the most frequent measurement of a particular environmental variable.

A numerical characteristic or measure obtained by using data from a sample.

Experimental Design & Analysis for Biological and Environmental Research.

Standard deviation.

To summarize data along with measures of central tendency.

Yes, statistics can vary depending on the sample taken.

Standard deviation and variance.

20% (10% for Topic 1-2 and 10% for Topic 3-4).

It is the group of elements from which data will actually be collected.

A ZERO mark will be given.

The sum of observations divided by the total number of observations.

Histograms are used for continuous data, while bar charts are used for categorical data.

The middle term when the data is arranged in ascending or descending order.

Mean, Median, and Mode.

Variability shows the spread of data, where 1 is less variable than 2.

A statistic is a numerical value that summarizes a characteristic of a sample.

It measures the variability or dispersion of a dataset, such as pollutant levels in a river.

The average of a set of numbers, calculated by dividing the sum of all values by the number of values.

A number describing a sample (e.g., sample mean).

30, as it is the middle value after arranging the data.

Evaluate and interpret statistical findings in scientific studies with critical thinking.

In a professional manner.

10 hours.

A presentation on assigned topics, followed by a Q&A session.

Data sets that include multiple variables, such as length, width, height, and volume of a rectangular box.

An individual project report discussing personal learning outcomes.

Practical statistical methods used in epidemiological studies.

A numerical characteristic or measure obtained by using all the data from a specific population.

A parameter is a numerical value that summarizes a characteristic of a population.

Average population size of a certain animal species based on a sample of counts.

The range of the middle 50% of the data.

By enabling appropriate decisions based on data analysis.

A dataset where all values are very similar, such as test scores of 90, 91, and 92.

Essential for making informed decisions and interpreting complex data.

No, parameters are fixed values for a given population.

Medicine, public health, and environmental science.

The value that appears most frequently in a data set.

2 quizzes.

The range of the middle half of a distribution.

50%.

To represent the distribution of numerical data.

Using bars that represent the frequency of data within specified intervals.

The value that occurs most frequently.

Continuous numerical data.

To describe the spread or dispersion of a dataset.

IQR = Q3 - Q1.

The degree of spread in the data set.

How far apart data points lie from each other and from the center of a distribution.

Medicine, Pharmacy, Biology, and Public Health.

The growth of plants under different light conditions.

Yes, statistics can vary depending on the sample taken.

6 hours of lecture and 3 hours of tutorial.

The 25th percentile.

Through graphs such as histograms or box plots.

They provide different insights into the data distribution and central tendency.

Using box and whisker plots.

Q4.

41 hours.

By applying statistical methods to health data to determine how often diseases occur in populations.

Experimental design and data analysis for biologists.

By communicating research findings and supporting hypotheses, giving credibility to research methodology and conclusions.

A branch of statistical science focused on the application of statistical methods to biological and health phenomena.

It provides methods for analyzing and interpreting numerical data relevant to these fields.

Parameters describe populations, while statistics describe samples.

Q1 is the first quartile and Q3 is the third quartile.

It indicates the difference between the highest and lowest values in a dataset.

It indicates that the data points are spread out over a wider range of values.

Range and interquartile range.

40 in each case.

The median is the average of the two middle values.

Multiple-choice and short-answer questions.

Interquartile range.

It is least affected by extreme values and focuses on the spread in the middle of the data set.

It helps in analyzing data to uncover potential causes and risk factors for diseases.

To ensure that new interventions are effective and safe for public use.

It indicates more variability in the data set.

Deng Dan.

In a right-skewed distribution, the tail extends to the right.

It helps summarize and describe the main features of a dataset.

The dispersion of the data set (variance, standard deviation).

By providing tools to analyze data and draw conclusions about environmental phenomena.

The entire group.

2 quizzes.

24 hours.

The average of squared distances from the mean.

Attendance must be greater than 80%.

Data analysis using IBM SPSS.

Categorical data.

Basic statistical concepts and their applicability.

By turning them into statistical questions.

Designing experiments with an appropriate statistical analysis plan.

The applicability of different measures.

It helps in assessing the reliability and consistency of data.

The application of statistics to biological and environmental research.

Gender, region, and religious affiliation.

The more spread the data, the larger the variance in relation to the mean.

Arrange the data in ascending order.

Parameters are numerical characteristics of a population, while statistics are numerical characteristics of a sample.

Check if the number of terms in the dataset is odd or even.

Using statistical measures such as range, variance, and standard deviation.

They help define the characteristics of the population being studied.

Standard deviation and variance.

The average distance from the mean.

To understand the relationship between variables and identify true effects.

Handbook of Environmental and Ecological Statistics.

Data sets that classify data into categories, such as male or female, married or unmarried.

By analyzing health data to assess overall health status and quality of life in populations.

The difference between the highest and lowest values.

A smaller group taken from the population.

Because they take the whole data set into account.

Introductory Biostatistics.

By analyzing data to quantify the impact of various risk factors on health outcomes.

Ability to identify biostatistics questions, characterize data properties, select analysis methods, perform analysis, interpret results, and critical thinking.

Biostatistics for Dummies.