Correlational and Experimental Hypothesis Testing
VerifiedAdded on 2023/06/11
|7
|1431
|181
AI Summary
This article discusses correlational and experimental hypothesis testing in psychology. It covers the steps involved in conducting a correlational study and an experimental study, as well as methods of data collection.
Contribute Materials
Your contribution can guide someone’s learning journey. Share your
documents today.
Running head: Correlational and Experimental Hypothesis Testing 1
Correlational and Experimental Hypothesis Testing.
Name
Institutional Affiliation
Correlational and Experimental Hypothesis Testing.
Name
Institutional Affiliation
Secure Best Marks with AI Grader
Need help grading? Try our AI Grader for instant feedback on your assignments.
Correlational and Experimental Hypothesis testing: 2
Introduction
Components of any organization or institution are groups or individuals who are engaged
into actions aiming at pursuance of common goals. Resources are therefore required for the day-
to-day running of the organizations. However, little or no attention has been paid to natural
elements that are freely available and could source much psychological and physiological
benefits to employees. A study was therefore conducted in attempt to bring into the limelight the
benefits that could accrue from exposure to green plants while trying to lower anxiety levels. A
hypothesis titled ‘Exposure to Green Plants Reduces People’s anxiety Levels’ was thereafter
formulated. The following two studies were later conducted to evaluate the hypothesis and
support it.
Correlational study.
Correlational study is aimed at determining the nature and the extent to which two
variables are related. Predictions can be therefore made basing on this relationship. To determine
the level of correlation between exposure to green plant and lowering in anxiety levels, the
following steps would be adopted. You will have to first have to formulate the null hypothesis
(H0) or the alternative hypothesis (Ha) (Startz, 2014). The null hypothesis indicates that there is
no correlation between the two variables. For you to support your hypothesis, you need to
identify an alternative hypothesis. It should however indicate positive correlation for it to be in
favor of your hypothesis. A one-tailed test or two tailed test could be used. (David A. Hensher,
Rose, & Greene, 2005)
You would thereafter need to choose the level of significance of the test. This is the
probability that you are going to reject the null hypothesis while it is actually true (Weakliem,
Introduction
Components of any organization or institution are groups or individuals who are engaged
into actions aiming at pursuance of common goals. Resources are therefore required for the day-
to-day running of the organizations. However, little or no attention has been paid to natural
elements that are freely available and could source much psychological and physiological
benefits to employees. A study was therefore conducted in attempt to bring into the limelight the
benefits that could accrue from exposure to green plants while trying to lower anxiety levels. A
hypothesis titled ‘Exposure to Green Plants Reduces People’s anxiety Levels’ was thereafter
formulated. The following two studies were later conducted to evaluate the hypothesis and
support it.
Correlational study.
Correlational study is aimed at determining the nature and the extent to which two
variables are related. Predictions can be therefore made basing on this relationship. To determine
the level of correlation between exposure to green plant and lowering in anxiety levels, the
following steps would be adopted. You will have to first have to formulate the null hypothesis
(H0) or the alternative hypothesis (Ha) (Startz, 2014). The null hypothesis indicates that there is
no correlation between the two variables. For you to support your hypothesis, you need to
identify an alternative hypothesis. It should however indicate positive correlation for it to be in
favor of your hypothesis. A one-tailed test or two tailed test could be used. (David A. Hensher,
Rose, & Greene, 2005)
You would thereafter need to choose the level of significance of the test. This is the
probability that you are going to reject the null hypothesis while it is actually true (Weakliem,
Correlational and Experimental Hypothesis testing: 3
2016). It is denoted as (α) alpha and for you to support your hypothesis, this value should be as
low as possible. A significance level of 0.06 for instance would indicate that there would be a
6% risk of making a conclusion that there a correlation between exposure to green plants and
reduction in anxiety levels. For a strong alternative hypothesis (positive correlation for your
case) to be obtained, the significance level should be low. (Shi & Tao, 2008)
The next step would be to choose the location of the critical region. This is the region
whose values, at a chosen probability level, corresponds to the rejection of the null hypothesis
(Singh, 2007). Assuming from research conducted previously, you were able to you are able to
isolate the value of critical region as z > 1.282. you will therefore proceed to compute the
statistics obtained in order to find the value of calculated z and make a comparison of the two.
Assuming twelve samples had been tabulated indicating a mean of 15.2 with a variance
of 2.5 in terms of anxiety levels reduction, from an area with a lower percentage of exposure to
green plants, results from another twelve sample indicates a mean of 16.8 from an area with a
relatively higher percentage of exposure to green plants. You are to determine whether it is worth
to increase percentage of exposure to green plants in attempt to reduce the levels of anxiety.
1. Formulation of hypotheses
H0 : = 15.2 (i.e. the mean of anxiety levels reduction to samples in an area with
higher percentage of exposure to green plants is equal to 15.2 and has a variance
of 2.5)
Ha : > 15.2 (i.e. the mean of anxiety levels reduction to samples in an area with
higher percentage of exposure to green plants is greater than 15.2)
2. Choose the level of significance
= 0.10.
2016). It is denoted as (α) alpha and for you to support your hypothesis, this value should be as
low as possible. A significance level of 0.06 for instance would indicate that there would be a
6% risk of making a conclusion that there a correlation between exposure to green plants and
reduction in anxiety levels. For a strong alternative hypothesis (positive correlation for your
case) to be obtained, the significance level should be low. (Shi & Tao, 2008)
The next step would be to choose the location of the critical region. This is the region
whose values, at a chosen probability level, corresponds to the rejection of the null hypothesis
(Singh, 2007). Assuming from research conducted previously, you were able to you are able to
isolate the value of critical region as z > 1.282. you will therefore proceed to compute the
statistics obtained in order to find the value of calculated z and make a comparison of the two.
Assuming twelve samples had been tabulated indicating a mean of 15.2 with a variance
of 2.5 in terms of anxiety levels reduction, from an area with a lower percentage of exposure to
green plants, results from another twelve sample indicates a mean of 16.8 from an area with a
relatively higher percentage of exposure to green plants. You are to determine whether it is worth
to increase percentage of exposure to green plants in attempt to reduce the levels of anxiety.
1. Formulation of hypotheses
H0 : = 15.2 (i.e. the mean of anxiety levels reduction to samples in an area with
higher percentage of exposure to green plants is equal to 15.2 and has a variance
of 2.5)
Ha : > 15.2 (i.e. the mean of anxiety levels reduction to samples in an area with
higher percentage of exposure to green plants is greater than 15.2)
2. Choose the level of significance
= 0.10.
Correlational and Experimental Hypothesis testing: 4
3. From previously tabulated data, we take the value of critical region to be;
z > 1.282
4. Proceed to computing statistics to obtain the calculated z
z= m−μ 0
s / √n
¿ 16.8−15.2
1.58
3.4641
= 3.51
(m represents the mean)
5. Make your conclusion based on results obtained from the step above
Because the calculated z = 3.51 > 1.282, the null hypothesis stating that the mean
level of anxiety reduction will be equal to 15.2 for samples exposed to higher
percentage of green plants. The mean level of anxiety reduction is greater than
15.2 and thus the alternative hypothesis would be opted.
Experimental study.
An experimental study will take into comparison the roles of the independent valuable in
determining the possibility of occurrence of the dependent variable (Poletiek, 2013). With the
independent variable being exposure to green plants, you will seek to determine how increasing
the percentage of exposure to green plants will increase the possibility that the anxiety levels of
the samples will reduce. The following is a sample set of data that could be used to display this
relationship.
Percentage of Percentage of
3. From previously tabulated data, we take the value of critical region to be;
z > 1.282
4. Proceed to computing statistics to obtain the calculated z
z= m−μ 0
s / √n
¿ 16.8−15.2
1.58
3.4641
= 3.51
(m represents the mean)
5. Make your conclusion based on results obtained from the step above
Because the calculated z = 3.51 > 1.282, the null hypothesis stating that the mean
level of anxiety reduction will be equal to 15.2 for samples exposed to higher
percentage of green plants. The mean level of anxiety reduction is greater than
15.2 and thus the alternative hypothesis would be opted.
Experimental study.
An experimental study will take into comparison the roles of the independent valuable in
determining the possibility of occurrence of the dependent variable (Poletiek, 2013). With the
independent variable being exposure to green plants, you will seek to determine how increasing
the percentage of exposure to green plants will increase the possibility that the anxiety levels of
the samples will reduce. The following is a sample set of data that could be used to display this
relationship.
Percentage of Percentage of
Secure Best Marks with AI Grader
Need help grading? Try our AI Grader for instant feedback on your assignments.
Correlational and Experimental Hypothesis testing: 5
exposure to green
plants
anxiety levels
reduction.
0 2
25 21
50 35
75 49
100 60
The above data could be easily presented in a line graph to vividly present the relationship
between the two variables. It will be noted that as the percentage of exposure increases, the
greater the percentage of anxiety reduction is reported from the samples and thus will be I
support of your hypothesis.
Methods of data collection.
A vast range of methods could be applied so as to obtain the above parameters to be used
in computations for the hypothesis test. Percentage of exposure to green plants could be obtained
by determining the percentage of green plants in the environment where the samples are found.
Samples could therefore be collected from environments with differing percentages in amounts
of green plants. Sample individuals could be interviewed to establish the percentage of anxiety
reduction. The following methods could therefore be of great relevance in establishing the values
of the parameters used: mail questionnaire, personal interview, case studies, opinionnaire or
observations (Olsen, 2011), (Guest, Namey, & Mitchell, 2012), (Braun, Clarke, & Gray, 2017).
The following are the techniques to apply in relation to the pre-mentioned methods; use of score-
cards and observational behavior scales, recording mass behavior, use of attitude scales,
exposure to green
plants
anxiety levels
reduction.
0 2
25 21
50 35
75 49
100 60
The above data could be easily presented in a line graph to vividly present the relationship
between the two variables. It will be noted that as the percentage of exposure increases, the
greater the percentage of anxiety reduction is reported from the samples and thus will be I
support of your hypothesis.
Methods of data collection.
A vast range of methods could be applied so as to obtain the above parameters to be used
in computations for the hypothesis test. Percentage of exposure to green plants could be obtained
by determining the percentage of green plants in the environment where the samples are found.
Samples could therefore be collected from environments with differing percentages in amounts
of green plants. Sample individuals could be interviewed to establish the percentage of anxiety
reduction. The following methods could therefore be of great relevance in establishing the values
of the parameters used: mail questionnaire, personal interview, case studies, opinionnaire or
observations (Olsen, 2011), (Guest, Namey, & Mitchell, 2012), (Braun, Clarke, & Gray, 2017).
The following are the techniques to apply in relation to the pre-mentioned methods; use of score-
cards and observational behavior scales, recording mass behavior, use of attitude scales,
Correlational and Experimental Hypothesis testing: 6
conducting both open and closed interviews. Small groups could be used to study random
behavior (Sapsford & Jupp, 2006).
conducting both open and closed interviews. Small groups could be used to study random
behavior (Sapsford & Jupp, 2006).
Correlational and Experimental Hypothesis testing: 7
Bibliography
Braun, V., Clarke, V., & Gray, D. (2017). Collecting Qualitative Data: A Practical Guide to
Textual, Media and Virtual Techniques. Cambridge University Press.
David A. Hensher, Rose, J. M., & Greene, W. H. (2005). Applied Choice Analysis: A Primer.
Cambridge University Press.
Guest, G., Namey, E. E., & Mitchell, M. L. (2012). Collecting Qualitative Data: A Field Manual
for Applied Research. SAGE Publications.
Olsen, W. (2011). Data Collection: Key Debates and Methods in Social Research. SAGE
publisher.
Poletiek, F. H. (2013). Hypothesis-testing Behaviour. Psychology Press.
Sapsford, R., & Jupp, V. (2006). Data Collection and Analysis. SAGE.
Shi, N.-Z., & Tao, J. (2008). Statistical Hypothesis Testing: Theory and Methods. World
Scientific.
Singh, K. (2007). Quantitative Social Research Methods. india: SAGE Publications.
Startz, R. (2014). Choosing the More Likely Hypothesis. Now Publishers.
Weakliem, D. L. (2016). Hypothesis Testing and Model Selection in the Social Sciences.
Guilford Publications.
Bibliography
Braun, V., Clarke, V., & Gray, D. (2017). Collecting Qualitative Data: A Practical Guide to
Textual, Media and Virtual Techniques. Cambridge University Press.
David A. Hensher, Rose, J. M., & Greene, W. H. (2005). Applied Choice Analysis: A Primer.
Cambridge University Press.
Guest, G., Namey, E. E., & Mitchell, M. L. (2012). Collecting Qualitative Data: A Field Manual
for Applied Research. SAGE Publications.
Olsen, W. (2011). Data Collection: Key Debates and Methods in Social Research. SAGE
publisher.
Poletiek, F. H. (2013). Hypothesis-testing Behaviour. Psychology Press.
Sapsford, R., & Jupp, V. (2006). Data Collection and Analysis. SAGE.
Shi, N.-Z., & Tao, J. (2008). Statistical Hypothesis Testing: Theory and Methods. World
Scientific.
Singh, K. (2007). Quantitative Social Research Methods. india: SAGE Publications.
Startz, R. (2014). Choosing the More Likely Hypothesis. Now Publishers.
Weakliem, D. L. (2016). Hypothesis Testing and Model Selection in the Social Sciences.
Guilford Publications.
1 out of 7
Related Documents
Your All-in-One AI-Powered Toolkit for Academic Success.
+13062052269
info@desklib.com
Available 24*7 on WhatsApp / Email
Unlock your academic potential
© 2024 | Zucol Services PVT LTD | All rights reserved.