Kimbrough_Lab Activity Scientific Method Skittles.docx

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University of Kansas *

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102

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Biology

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Feb 20, 2024

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Lab Activity BIOL 102 Lab Activity – Scientific Method Data Analysis and Conclusions Learning Objectives: Use the scientific method including making observations, identifying variables and controls, collecting, and analyzing data and drawing conclusions. Use basic calculations to analyze data: means, p-values. Summary: In this lab we will use the process of the scientific method to determine if smell improves a person’s ability to identify the flavor of candy. We will start with observations, generate questions, perform an experiment, conduct data analysis, and validate our hypothesis. Materials Needed for Lab The following materials are needed to complete this lab. Calculator / Excel / Google sheets Graphpad.com Class Excel Data Sheet Scientific Method Spring 2024-1 1
Lab Activity BIOL 102 Results and Analysis YOU NEED TO COMBINE YOUR DATA WITH THE CLASS DATA FOR THIS PORTION OF THE LAB Step 1. Navigate to the assignment in Canvas. Download the Excel file and open the class data sheet. Step 2. Save the Excel file to your computer. Step 3: Add your data from the pre-lab to the Excel file. The data to be transferred to the Excel sheet are the data tabulated in the correct response columns. Step 4. Use all data for data analysis when completing activities below. Activity 1 – Calculating the Mean (Average) Using the class data and your data from the pre-lab, calculate the mean (average) for each color of candy tested, and record your results in Table 1. To calculate the mean, follow the formula and example below. Note that our mean will be a value between 0 and 1, as our responses were 0 (for incorrect) and 1 (for correct). Formula: Mean = (sum of responses)/ N; where N = total number of participants Mean (correct red) = sum of correct responses for red / total number of participants Mean = 48 / 65 = 0.457 Scientific Method Spring 2024-1 2
Lab Activity BIOL 102 Activity 2 – Graphing Our Results Using your data in Table 1, you will create a bar graph (example below) that shows the mean of the correct responses for the control group (eyes closed) and the treatment group (eyes closed and nose plugged) for each flavor of candy tested. 1. The x-axis is the category – control or treatment group 2. The y-axis is the mean of the correct responses. 3. Make sure to label the x-axis, y-axis and give your graph a descriptive title. 4. Insert or copy your graph in the Assignment – Exit Ticket Section. ** Example only – your title, values for means and total number of tasters may be different. You may use your preferred graphing software (Excel, Numbers, Google Sheets, or Chart tool in MS Word) to create your bar graphs. You may also draw them by hand on paper and submit photos of your graphs. Activity 3 – Calculating the p-Value for Hypothesis Testing We will use a t-test (a statistical test) to analyze our data to determine if our hypothesis is supported. Follow the steps below to use graphpad.com to use a t-test calculator to find the p-value. The p-value will determine if there is a significant difference between the means for the control and treatment groups. Scientific Method Spring 2024-1 3
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Lab Activity BIOL 102 Steps to calculate the p-value. Proceed through the steps as outlined below and refer to Figures 1 and 2 as needed. To Start: Open the t-test calculator on graphpad.com using the link below. The screen should look like the screen in Figure 1 below; you do not need to sign up or create an account to use QuickCalcs. Graphpad T-Test Calculator Step 1. On the left-hand side of the screen find step 1. Choose data entry format select Enter or paste up to 2000 rows . Step 2. – On the left-hand side of the screen locate step 2. Enter Data. Above the two columns there are two fields for Label . Initially the labels should say “Group 1” and Group 2”. We are going to change these to correspond to the condition tested. Change “Group 1” to “Control" and “Group 2” to “Experimental”. Step 3 . Enter the class results from the Excel sheet for the correct color in the corresponding data columns. You will be copying and pasting data from this spreadsheet into the large cells under the Red-correct and Red-incorrect groups. Use the data for all participants available. Step 4 . On the right-hand side of the screen, find step 4 . Choose a test and select Paired t test. Step 5. On the right-hand side of the screen, find Step 5 . View the results and click on Calculate now. A new window titled Paired t-test results will appear as shown in Figure 2, will appear. Step 6 . Under p-value and statistical significance , locate the p-value (Figure 2). Record this result in Tables 4a-c at the end of the document. Step 7 . Locate Review your data, use this information to check your answers in Table 2 for mean and N (number of participants). Step 8 . Repeat steps 1-5 for each of the remaining candies tested and record in the corresponding figure. Figure 1. Steps to follow in QuickCalcs. Scientific Method Spring 2024-1 4
Lab Activity BIOL 102 Figure 2. Reading Paired t test results in QuickCalcs - Finding P-value, Mean and N (number of participants) Scientific Method Spring 2024-1 5
Lab Activity BIOL 102 Activity 4 – Statistical Significance, Hypothesis Testing and Conclusions Now that we have conducted our experiment, calculated means, and graphed our responses; we will want to know what conclusions we can make from our experiment. In this next section, we will learn how to use the p-value and mean responses to determine if your results support or reject the null hypothesis. Statistical Significance What does Statistical significance mean? To answer that, let’s return to the null hypothesis: There is no difference in a taster’s ability to identify the flavor of Skittles® based on taste and smell and taste alone. Our results will either support or reject this hypothesis. We may find that with our eyes closed, nose plugged, the number of people who taste the candy and correctly identify the flavor is equal to the number of people who taste the same candy and correctly identify the flavor with only eyes closed. In this case, the average for both flavor identification outcomes would be the same and we would support the null hypothesis. Conversely, if we found that the number of people correctly identified the flavor with just eyes closed was not equal to the number of people that identify the flavor with eyes closed and nose plugged, we would reject our hypothesis. When you first look at your data, you may see that all the means within each color-flavor category appear to be different. However, are all these differences real? How large must a difference between the means be for us to say that the difference is real? We may be fairly confident that the difference between an average of 0.7 and an average 0.3 is real. But what if it is not that obvious. Is the difference between two close averages, say 0.57 and 0.43 real? Is it due to chance and small enough to be inconsequential? Here is where statistical significance helps determine the answer to that question in a non-arbitrary and consistent manner. A p-value > 0.05 is considered statistically insignificant meaning the difference is not real. However, p-values < 0.05 indicate that the difference is real, i.e., statistically significant. Let’s apply this idea of statistical significance to our results. For candy flavors that had a p-value > 0.05 we can conclude there is no significant difference between the two identification outcomes. The number of people that correctly identified the flavor with their eyes closed and nose plugged was equal to the number of people that correctly identified the flavor with only their eyes closed. For color-flavor categories that had a p-value < 0.05, the number of people that identified the candy flavor correctly with eyes closed, nose plugged is statistically different than the number of people that identified the candy flavor with only eyes closed. If a greater number of people identified the flavor correctly using taste and smell, we would report there is evidence to suggest that smell improves the ability to identify the flavor correctly. Scientific Method Spring 2024-1 6
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Lab Activity BIOL 102 Hypothesis Testing For the next step, hypothesis testing, we will use the decision tree (refer to Figure 3) with our calculated p-values to determine whether your results support or reject the null hypothesis. Figure 3. Decision tree used for hypothesis testing. Writing the Conclusion The conclusion is a paragraph that contains a description of the purpose of the experiment, a discussion of your major findings and an explanation of your findings. Use this as a guideline for writing your conclusions for all labs in the course. o State the overall purpose of the lab; include the independent and dependent variables. Scientific Method Spring 2024-1 7
Lab Activity BIOL 102 o State whether the hypothesis was rejected or not; include the p-value o Summarize the results of your data from your graph and tables that support your statement regarding the hypothesis. Include the values of the means (averages) for the control group and the treatment group. o Discuss the importance of the results, does smell improve one’s ability to identify the flavor or not? Assignment Exit Ticket Directions: 1. Complete Activities 1-5 2. Submit your assignment in Canvas; it must be in .pdf format. Name: Ben Kimbrough Student ID: 3014821 Date : Jan 19 2024 Activity 1. Calculating the Mean Table 1. Class Results of Eyes Closed Nose Plugged and Eyes Closed Tasting of Candy. Only include mean responses for correct answers. Lime - Green Strawberry - Red Lemon-Yellow Control Group Eyes Closed Experimental Group Eyes Closed and Nose Plugged Control Group Eyes Closed Experimental Group Eyes Closed and Nose Plugged Control Group Eyes Closed Experimental Group Eyes Closed and Nose Plugged Sum of Responses 43 21 27 16 50 13 N (Total Number of Participants) 65 65 65 65 65 65 Scientific Method Spring 2024-1 8
Lab Activity BIOL 102 Mean .66 .32 0.42 0.25 .77 .20 Activity 2. Graphing our Results Insert your graphs here. Include all required elements. Activity 3 and 4. P-values, Hypothesis Testing and Conclusions For each flavor candy, use the p-values and the decision tree in Figure 4 to determine statistical significance and whether your results for this flavor fail to reject or reject the null hypothesis. Write a brief conclusion about smell and flavor for each candy. Record all the above in Tables 4a-c. Conclusions must use complete sentences. Table 4a. Lime – Green Conclusions Lime - Green p-value .0044 Hypothesis Testing: Is your p-value 0.05 OR < 0.05 ? Using the p-value, is the Null Hypothesis “Not rejected” or “Rejected”? Refer to the hypothesis testing decision tree. My p-value is greater than 0.05, meaning our Null hypothesis is not rejected. Scientific Method Spring 2024-1 9
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Lab Activity BIOL 102 Conclusion: Using complete sentences write a conclusion regarding the relationship between smell and flavor. Include data (p-values and means) to support your answer. Because our p-value was so close to the 0.05 stated in the text I think that there could and could not be a difference between smell and flavor. Personally I think that it varies from person to person, but our data shows that there is a difference. Table 4b. Strawberry - Red conclusions Strawberry - Red Candy p-value 0.0702 Hypothesis Testing: Is your p-value 0.05 OR < 0.05 ? Using the p-value, is the Null Hypothesis “Not rejected” or “Rejected”? Refer to the hypothesis testing decision tree. My p-value is greater than 0.05, meaning our Null hypothesis is not rejected. Conclusion: Using complete sentences write a conclusion regarding the relationship between smell and flavor. Include data (p-values and means) to support your answer. Because our p-value was greater than 0.05, that means there is no relationship between smell and flavor. It is over two tenths the testing number of 0.05, so our hypothesis could remain true. Scientific Method Spring 2024-1 10
Lab Activity BIOL 102 Table 4c. Lemon - Yellow conclusions Lemon – Yellow Candy p-value .0001 Hypothesis Testing: Is your p-value 0.05 OR < 0.05 ? Using the p-value, is the Null Hypothesis “Not rejected” or “Rejected”? Refer to the hypothesis testing decision tree. Since it is less than 0.05 the Null Hypothesis is rejected Conclusion: Using complete sentences write a conclusion regarding the relationship between smell and flavor. Include data (p-values and means) to support your answer. Because there is a large gap between the yellow skittle p-value and 0.05, this possibly means that there could be a difference between the controlled and experimental value, meaning that we need to create a new hypothesis. Activity 5: Sources of Error 1. From our experiment, can we conclude that ALL Skittles® flavors in the red bag require olfactory senses (sense of smell) to identify the flavor? Consider the design of the experiment and our results of the study. You cannot determine that because we only did three of the flavors from the bag, and depending on the person the results can vary. I think we can determine that some of the colors require olfactory senses, but we cannot determine that for every single color 2. Sources of error are a result of human and equipment errors. For this experiment, discuss in detail one source of error. Include how that error affected the results and how this error could be minimized or eliminated. These may be errors with the laboratory procedure itself. One place of error that might have occurred in my experiment is some of my individuals guessed on the color, without having any clue what it might be. They said that they couldn’t tell what flavor it was and just picked a random one, and sometimes they got it right. Scientific Method Spring 2024-1 11