Quantitative Research SOHP503 Project
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What was the effect of the intervention on health-related quality of life in comparison to the control arm?

  • There was no difference between the groups.
  • The control arm showed greater health-related quality of life improvement.
  • The intervention significantly decreased health-related quality of life.
  • The intervention improved health-related quality of life. (correct)

    • What was the significance level (p-value) for the between-arm difference in health-related quality of life?

  • p = 0.04 (correct)
  • p = 0.05
  • p = 0.03
  • p = 0.01

    • What can be concluded about the glycated hemoglobin levels between the groups?

  • They differed but the difference was not significant. (correct)
  • They were not measured.
  • They were significantly different.
  • The intervention group showed lower levels.

    • Given the findings, what is true about the meaningfulness of the significant difference in health-related quality of life?

    <p>The difference was statistically significant but not meaningful. (C)</p> Signup and view all the answers

    What information is lacking regarding the sample size in the study?

    <p>Whether the sample size was large enough is unknown. (D)</p> Signup and view all the answers

    What is a key aspect of virtual meeting etiquette for SoHP503?

    <p>Dress appropriately and ensure your surroundings are tidy. (D)</p> Signup and view all the answers

    Which of the following is NOT a learning objective for understanding quantitative data?

    <p>Collect data from qualitative sources. (C)</p> Signup and view all the answers

    In the context of numerical importance, what does a score of 5/10 indicate?

    <p>Represents 50% of students scoring at least this amount. (A)</p> Signup and view all the answers

    What is the main advantage of using a scatter plot over a frequency table when representing two numerical variables?

    <p>Scatter plots make it easier to identify trends and relationships. (B)</p> Signup and view all the answers

    What is essential when positioning your camera in a virtual meeting?

    <p>Ensuring your entire head is visible. (B)</p> Signup and view all the answers

    In the context of the provided data, what should be done if the scatter plot is too crowded?

    <p>Use a frequency table to present the data more clearly. (D)</p> Signup and view all the answers

    Which statement best describes the importance of numerical context in data representation?

    <p>It adds depth and relevance through proper scoring context. (D)</p> Signup and view all the answers

    Which data types are represented effectively in a scatter plot according to the information given?

    <p>Two numerical variables and one categorical variable. (C)</p> Signup and view all the answers

    What is the highest individual score mentioned in the context of different scoring systems?

    <p>15/100 (B)</p> Signup and view all the answers

    What is indicated by a score of 5/100?

    <p>At least half of students achieved a score higher than this. (C)</p> Signup and view all the answers

    What is a recommended practice if a scatter plot is overly complicated because of too many categories?

    <p>Create separate scatter plots for each category. (B)</p> Signup and view all the answers

    What practice is advised when not actively speaking during a virtual meeting?

    <p>Mute your microphone to avoid background noise. (A)</p> Signup and view all the answers

    If a dataset includes age and height data along with eye color, what kind of plot would best demonstrate relationships among these variables?

    <p>A scatter plot with color-coded categories for eye color. (B)</p> Signup and view all the answers

    When is it appropriate to choose a table over a scatter plot for data representation?

    <p>When clear comparison among multiple categories is needed. (C)</p> Signup and view all the answers

    Which conclusion can be drawn about the use of scatter plots from the data?

    <p>They can display two numerical variables with an added categorical dimension. (D)</p> Signup and view all the answers

    What specific data does the scatter plot mentioned suggest for eye color categorization?

    <p>Eye color categories should be colored in the scatter plot. (D)</p> Signup and view all the answers

    Which of the following statements best defines numerical data?

    <p>Data that is quantifiable and expressed in numbers (D)</p> Signup and view all the answers

    What does ordinal data represent?

    <p>Ordered narrative data with rankings (B)</p> Signup and view all the answers

    Which of the following is NOT a common descriptive analysis technique?

    <p>Variance (A)</p> Signup and view all the answers

    In a frequency table regarding eye color and likeliness to watch horror movies, what does a count represent?

    <p>The number of times each eye color category appears in relation to horror movie preferences (D)</p> Signup and view all the answers

    How does nominal data differ from ordinal data?

    <p>Nominal data consists of non-ordered categories, while ordinal data involves ranking. (C)</p> Signup and view all the answers

    What was the primary objective of the study involving the My Diabetes Coach app?

    <p>To evaluate the effectiveness of the app for diabetes self-management. (A)</p> Signup and view all the answers

    Which method would best express the concept of central tendency?

    <p>The mode of a set of data (C)</p> Signup and view all the answers

    Which outcome measure was NOT included in the study?

    <p>Weight loss percentage (D)</p> Signup and view all the answers

    When analyzing likeliness to watch horror movies using a cross-tab frequency table, what key characteristic is being assessed?

    <p>The correlation between two categorical variables (B)</p> Signup and view all the answers

    What was the total number of adults randomized in the study?

    <p>187 adults (A)</p> Signup and view all the answers

    Which example best illustrates nominal data?

    <p>Colors of cars owned (C)</p> Signup and view all the answers

    What is the primary function of descriptive statistics?

    <p>To describe and summarize the collected data (A)</p> Signup and view all the answers

    What was the main finding regarding the change in HbA1c levels between the intervention and control groups?

    <p>Both groups showed reductions, but the difference was not statistically significant. (D)</p> Signup and view all the answers

    What was the observed change in health-related quality of life (HRQoL) in the intervention arm?

    <p>HRQoL scores improved compared to the control arm. (A)</p> Signup and view all the answers

    Frequency analysis in research is primarily concerned with what aspect of data?

    <p>Counting how many times each value occurs (A)</p> Signup and view all the answers

    How long was the duration of the study tracking the app's effectiveness?

    <p>12 months (A)</p> Signup and view all the answers

    What was the p-value associated with the change in HbA1c indicating its statistical significance?

    <p>p = 0.83 (A)</p> Signup and view all the answers

    How were the adults with type 2 diabetes allocated to either group in the study?

    <p>They were randomized into intervention and control arms. (B)</p> Signup and view all the answers

    What does a significant p-value indicate in a statistical analysis?

    <p>There is a statistically significant difference. (B)</p> Signup and view all the answers

    Which condition is necessary for applying parametric tests?

    <p>Data is linear. (C)</p> Signup and view all the answers

    What does a correlation coefficient of 0.9 indicate?

    <p>A strong positive correlation. (B)</p> Signup and view all the answers

    Which of the following statements is true regarding correlation and causation?

    <p>Correlation does not imply causation. (D)</p> Signup and view all the answers

    What is a primary assumption for performing a t-test?

    <p>The data must meet normality assumptions. (D)</p> Signup and view all the answers

    In a scatter plot representing a positive correlation, what is the expected relationship between the variables?

    <p>Both variables increase together. (B)</p> Signup and view all the answers

    What characterizes non-parametric statistics compared to parametric statistics?

    <p>They do not require a linear relationship. (A)</p> Signup and view all the answers

    What would be an example of a strong negative correlation?

    <p>-0.9 (D)</p> Signup and view all the answers

    In correlation research, what must be avoided regarding the relationship of data points?

    <p>Data should not have multiple directional relationships. (C)</p> Signup and view all the answers

    Which of the following is NOT an assumption for Pearson’s r?

    <p>Data is not normally distributed. (C)</p> Signup and view all the answers

    What distinguishes a significant p-value from a practically useful difference?

    <p>Significant p-value concerns statistical relevance, while practical difference is about real-world application. (A)</p> Signup and view all the answers

    What describes the difference between a significant difference and a meaningful difference?

    <p>Significant difference refers to statistical findings, while meaningful difference relates to practical usefulness. (A)</p> Signup and view all the answers

    Study Notes

    Quantitative Research SoHP503 Project Studies

    • The presentation is given by Dr. Krithika Anil, a Research Fellow at the University of Plymouth.
    • The course code is SOHP503, and it's about quantitative research.

    Virtual Meeting Etiquette

    • Turn off your phone.
    • Leave the keyboard alone unless using it for chat or activity.
    • Dress appropriately (no pajamas).
    • Be mindful of your surroundings (no messy rooms, inappropriate posters/backgrounds).
    • Mute your microphone when not talking.
    • Speak up, and stay seated and present. Position camera to show full head, not just forehead, chest or room.

    What is this lecture about?

    • Students have collected quantitative data, and the lecture outlines the next steps.
    • Learning objectives include understanding and applying descriptive statistical techniques to data, presenting the data correctly, acquiring and applying inferential statistical techniques, and critically assessing statistically appropriate techniques applicable to the research aim.

    What makes numbers important?

    • Numerical scores (e.g., 5/5, 5/10, 5/100) are used in various contexts and show important information.
    • Examples presented include student scores (and their percentage relation), with the highest marks for the given scores given.
    • Pain score data is presented as an example showing how numbers can show a context like pain.
    • Numbers allow for the report of numerical context and illustrate analysis, showing various numerical contexts.

    Data type

    • Data can be numerical (e.g., height, number of patients, walking speed, assessment score)
    • Data can be ordinal (e.g., rankings, satisfaction rating, spice tolerance)
    • Data can be nominal (e.g., preferences, nationality, hair colour)

    Descriptive statistics

    • Describes the collected data.
    • Analysis techniques include frequency, central tendency (mean, median, mode), distribution, and mean difference.

    Descriptive statistics – Frequency

    • A frequency table is a way to show how often each value appears for a categorical variable.
    • Example used likeliness to watch horror films and eye colour.

    Descriptive statistics - Frequency (Cross-tab)

    • A cross-tab frequency table is given to explain cross-tabulated data.
    • An example presents likeliness to watch horror and eye colour, showing that different percentages of people of different eye colours had different levels of likeliness to watch horror.
    • Bar charts are also given as alternative data display. Use of tables and graphs is suggested in the case of too many variables.

    Descriptive statistics - Frequency (Two numerical variables)

    • Example relating height and age shows frequency tables and scatter plots, with the scatter plot being a better visual for the data since it is easier to understand.
    • Example presents data with relation to height, age and different eye colours, in a scatterplot graph.

    Descriptive statistics - Central tendency

    • Describes the centre point of a dataset.
    • Techniques include mean (sum of values divided by total values), median (middle value in ascending order), and mode (most frequent value).
    • Example data is presented in relation to mean, median and mode calculations.

    Descriptive statistics - Distribution

    • Shows the spread and patterns in the data.
    • Includes normal distribution (symmetrical shape), skewed distribution (asymmetrical shape showing whether data is more spread out on one side than the other).
    • Methods include histograms, normal / skewed data plots and boxplots along with spread of data descriptions.

    Descriptive statistics - Distribution (Standard deviation)

    • Standard deviation (SD) shows the spread of data around the mean.
    • The further data points are from the mean, the higher the SD, showing that the data is more spread out.
    • Examples related to the spread of data are presented
    • Examples for standard deviation and normal distribution is given.

    Descriptive statistics - Distribution (Different types)

    • Data can be normal distribution, or skewed.
    • Example presentations of small vs large spread of data showing how the graphs look

    Descriptive statistics - Distribution (IQR)

    • SD isn't always the best for skewed distributions.
    • IQR (interquartile range) is better for identifying spread in middle half of data.
    • Median and Q1 and Q3 values are given to illustrate skewed distribution and calculation thereof as an alternative to standard deviation.

    Descriptive statistics - Mean difference

    • Compares the means of two groups.
    • Helps determine the effect size.
    • Example of how comparing two different groups / populations is able to give a mean difference.

    Inferential statistics

    • Makes assumptions/ inferences about population using sample data.
    • Techniques include correlation, T-test, and ANOVA.

    Inferential statistics - Sample Size

    • Importance of sample sizes in inferential statistics
    • It is important that sample size is large enough for making appropriate inferences and creating reliable results.
    • Example of how small sample size can affect results

    Inferential statistics - P-value

    • Indicates the likelihood of an outcome happening by chance.
    • Helps assess whether difference between groups is significant (e.g., by rejecting the null hypothesis)
    • A p-value does not mean that the research hypothesis is valid.

    Inferential statistics - Parametric and Non-Parametric variables

    • Parametric tests rely on data meeting certain assumptions (e.g., normally distributed, linear).
    • Non-parametric tests do not have as many assumptions, but may need larger samples

    Inferential statistics - Correlation

    • Shows extent to which variables move together (positive, negative, or no correlation).
    • Illustrates that correlation does not mean causation; A change in one variable does not necessarily cause the change in the other variable.

    Inferential statistics - Correlation (Scatter Plots and Pearson's r)

    • Scatter plots are graphs helpful for seeing correlations.
    • Pearson's correlation coefficient shows the strength and direction of the relationship, with values between -1 and 1.

    Inferential statistics - T-test

    • Compares means of two groups.

    Inferential statistics - ANOVA

    • Compares means of more than two groups.
    • Types of ANOVAs are also discussed in relations to single or multiple variables.

    Activity - Practical Example (Type 2 Diabetes Intervention Using a Mobile App)

    • This relates a description of practical example of the use of Quantitative research.
    • Includes the objective, methods, and results of the study.

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    Quantitative Research SoHP503 Project Studies PDF

    Description

    Join Dr. Krithika Anil for an insightful session on quantitative research as part of the SOHP503 course. This presentation covers the next steps for analyzing data collected by students, focusing on descriptive and inferential statistics, and best practices for effective data presentation.

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