Hi Sana, One-Way ANOVA: An ANOVA hypothesis tests the difference in population means based on one characteristic or factor. a----->b "An example of when a one-way ANOVA could be used is if you want to determine if there is a difference in the mean height of stalks of three different types of seeds. Since there is more than one mean, you can use a one-way ANOVA since there is only one factor that could be making the heights different. " Two-Way ANOVA: An ANOVA hypothesis tests comparisons between populations based on multiple characteristics. a---->cc, b------>d, a----->d, b----->c http://www4.uwsp.edu/psych/cw/statmanual/manovauses.html Good luck!

Hi Sana, One-Way ANOVA: An ANOVA hypothesis tests the difference in population means based on one characteristic or factor. a----->b "An example of when a one-way ANOVA could be used is if you want to determine if there is a difference in the mean height of stalks of three different types of seeds. Since there is more than one mean, you can use a one-way ANOVA since there is only one factor that could be making the heights different. " Two-Way ANOVA: An ANOVA hypothesis tests comparisons between populations based on multiple characteristics. a---->cc, b------>d, a----->d, b----->c http://www4.uwsp.edu/psych/cw/statmanual/manovauses.html Good luck!

When to use different test, this will surely guide you... its simple and to-the-point:

http://www.sfu.ca/~ber1/iat802/pdfs/When%20to%20use%20what%20test.pdf

Interesting questions and defenitely informative answers and links - I usually would depend on FIELD's book whenever I analyse my data... great step by step! Field uses some interesting examples - that would make you laugh - and makes the analysis easier!? hahah

Regards

Theodora Issa

Here is the citation for this book... especially if you are using SPSS for the benefit of the readers...

Field, A. (2005). Discovering Statistics Using SPSS (2nd ed.). London: Sage Publication.

Might have a new edition!?

Regards

Theodora Issa

Thanks Henna, the link you provide is very useful and really helps to decide when to use different statistical test.

You are most welcome Yahya, see this link its very useful for statistics & related info

http://www.sfu.ca/~ber1/iat802/

Good luck with your work.

Regards

Theodora Issa

1 way is using 1 factor (independent variable); 2 way you need 2 factors (is important de cross effect, if you doesn't find it the 2way analysis doesn't worth it. Is the same doing two separated 1way analysis).

Finallly, MANOVA is for working with at least two dependent variables at the same time.

MANOVA can be thought of as using the output of a factor or principal components analysis of two or more variables (i.e., sort of like a factor or PC score) as the dependent variable in what then becomes a regular one- or two way ANOVA.

I am illiterate when it comes to biostatistics. My question is if I am treating my cells with different concentrations of several different drugs then which ANOVA should I use: One way, two way without replication or two way with replication?. Please help. And I already very confused, so easy answers please. 

Hello Sana Haroon and Sonal Mundhra.. kindly follow the attached link http://wikieducator.org/images/f/fb/Stats_11_ANOVA.pdf

To Sonal's question: It depend on what your doing with the cells. If you have three concentrations of whatever, and you have an interval level outcome, a one way ANOVA would be appropriate.  If you're going to treat them once and then again, then you need to model replication. But if all you're doing is the former, one-way ANOVA is fine.  Good luck.

Which type of ANOVA (one way or two way) is suitable if I want to compare the effect of 3 different fertilizer (A, B, C for example) with 3 different amount (1, 10, 100 Kg/ha for example) on the mean height of stalks?

2-way ANOVA

2-way ANOVA

2-way ANOVA

2-way ANOVA Seyed Ali Johari

One-way ANOVA: Comparing  three or more than three means of the independent samples (unmatched data) from the Populations with the same mean (i.e yield of rice per acre for three types of rice seeds)

2-way ANOVA: Comparing three or more than three means for the samples (Matched set of data) from the Populations with the same means adding another variable.

(i.e yield of rice per acre for three types of rice seeds adding 04 types of fertilizers)

Example:-

• The types of lines/genotypes could cause the change,  the types of moisture levels could cause the change, and/or  there is an interaction between the type of lines/genotypes and the type of moisture levels.
• There are two factors here (type of lines/genotypes and moisture levels), so, if the assumptions hold, then you can use a two-way ANOVA.

I am trying to see the effects of a protein and its three different mutants on phosphorylation of another protein (the phosphorylation of which can go up or down). What ANOVA should I use? one way or two way?

@Nisha, that is a typical ONE way ANOVA,if your measurement is not dependent on the time.  However, if you measure it on multiple days, you can do two way ANOVA as well.  Each day will be a block. 

What if I want to evaluate the effect of two types of silicon with three different concentrations each on the mean height of plants? Each treatment has 5 replicates. Should I use one way or two way ANOVA?

That should be a two way ANOVA,  types of silicon are the "rows", and three concentrations/treatments are the "columns". 

Thank you Feng Gao.

sorry to bump this thread but i am also confused on which ANOVA to use.

i have two groups of children with different skeletal pattern, I want to confirm the difference in breathing habits when the test group uses an appliance which the control groups will not use, for one of the results i have three parameters to confirm statistical difference, which ANOVA should I use?

Cynthia... when you talk about "three parameters", do you mean "factors"? if yes, just a 3-way ANOVA or maybe a repeated anova may be useful to solve your problem...

Dear all,

Thank you for giving your time in elaborating the basic questions that I also learnt a lot.

Dear all,

Thank you for giving your time in elaborating the basic questions that I also learnt a lot.

Dear all,

I want to test the difference of fatigue for 5 muscles at 2 different saddle height,

I have 10 subjects, 5 muscles EMG recording from each subject, 2 cycling test at different saddle height.

I'm using one way ANOVA to test my data, the data for one muscle grouped by 2 columns (saddle 1, saddle 2) the rows are data for all subjects, so I have 5 anova test one for each muscle.

is that correct ? do I need to do it in a different way ?

I also have one question about type of ANOVA. 

I'm doing research about signalling and impact of signalling on quality of experience. 

If I have two independent variables (prioritization algorithm and load) and two dependent variables (experience for prioritatization and experience for load), which Anova to use? 

HI everyone,

I am doing research on keratin involvement on insulin signaling pathway. 

I want to do a statistic test, i have two type cells, type A and type B. I made 3 experiments (3 data per experiment), for each experiment i did 6 different treatment for each type of cells. I want to compare the result (vesicle volume) between A and B cells of each treatment (6) and between A and A, B and B, A and B between different treatments. I don't known if i am very clear but which test should i take? Thank you a lot for your help.

Maybe a repeated ANOVA??

repeated ANOVA you mean two-way ANOVA?

Thanks

Nop.... two-way ANOVA is when you have two factors but, if understand correctly, you have more than two factors. Other way could be multivariate ANOVA. If you are familiarized with Matlab, check the function anovan. Repetitive ANOVA is also available as ranova but until from the version 2016....

Thank you for your help. I don't have Matlab but i have prism 7 do you know if it is possible with this software? I'll try to figure it out. Thank you.

Sorry Alexandra. .. I don't know that software....

Let me take a short. I think alexandra is having data set with two factors that is the cell type and experiment type (  1 to 6). Vesicle volume is the dependent variable will be classified under cell type and experiments. A two factor ANOVA should work if the factor experiment levels is not considered. A repeated ANOVA may be ideal case if you the groups are related and the groups exhibit high correlation between them. I think as u r working with two different samples u can actually assume independence so for a for between the subject ANOVA and not repeated ANOVA.

Correct me if I am wrong

Hi there, 

If anyone can please advise me if I can justify using a 1-way ANOVA vs. a 2-way ANOVA. We are interested in the effects of alcohol exposure on individual zebrafish auditory organs. Can we justify using a 1-way ANOVA since there was only one factor that could be making the sizes different (alcohol exposure at different times periods)?

For each fish we measured body length, vesicle size and ear stone size at 3 time points.

We ran individual 1-way ANOVAs for each day (3,5, and 7 dpf). 

We were not interested in differences between days (i.e. between 3 and 5 dpf and/or between 5 and 7 dpf).  

Thank you kindly for any advice.

Lilliann, I don't understand 100% the description of your experiment, but you can be sure that one factor does mean 1-way ANOVA....

Hi,

Combined analysis.

see, 

http://www.iasri.res.in/ebook/ebadat/2-Basic%20Statistical%20Techniques/15-COMBINED-ANALYSIS.pdf

hope it help.

Greeting. I agree with my colleague Puska.

 I agree with Ufuk Turen.

 Ufuk Turen has given an opt reply and to add to it, it is always advisable to select the correct independent variables that influence the relationship with dependent variables and then apply suitable ANOVA testing.Because only an appropriate Ind.variable selected for the analysis makes more meaningful data analysis.

 Ufuk Turen has given an opt reply and to add to it, it is always advisable to select the correct independent variables that influence the relationship with dependent variables and then apply suitable ANOVA testing.Because only an appropriate Ind.variable selected for the analysis makes more meaningful data analysis.

 Ufuk Turen has given an opt reply and to add to it, it is always advisable to select the correct independent variables that influence the relationship with dependent variables and then apply suitable ANOVA testing.Because only an appropriate Ind.variable selected for the analysis makes more meaningful data analysis.

Hi there,

I'd be so grateful if someone could help me out with this: I will be testing whether or not seals can hear the sound of three types of acoustic deterrent devices (or pingers).

I will carry out about 15 sessions (1 session = 30 trials). There will be 4 possible outcomes in each trial (correct detection, correct rejection, incorrect detection, incorrect rejection) and at the end of each session I will have a total number of occurrences for each of the 4 outcomes. So in the end I will have data for these 4 outcomes for 15 sessions for 3 different types of pinger and for 3 different seals.

I basically want to know whether these pinger sounds are audible or not. Then I would like to compare between the 3 pingers and perhaps also compare audibility across individuals.

I was thinking of using a one-way ANOVA but I'm not sure if it should be a two-way ANOVA instead?

Thanks a lot in advance!

Andrea

It seems that you have three factors:

Factor 1: Outcome, with 4 levels

Factor 2: Type of Pinger, with 3 levels

Factor 3: Seal, with 3 levels.

If you aren't interested to check the effect of the factor 3 (seal), I think that using a two-way ANOVA is OK, but, if you want to include seals (or any other third factor in general terms), there is a N-ways function in Matlab that can help you (anovan). However, from my personal point of view, it would be more interesting doing the analysis only with Factor 1 and Factor 2; including Factor 3 may entail an "out of memory" error. You can also do the two-ways ANOVA analysis with anovan. It's a very friendly function to work...

I hope it helps...

Sorry to jump in on this but im doing a research paper where I am comparing males and females estimates on their own iq, their mothers and their fathers. So one Independent variable and 1 dependant variable with 3 levels. Would this be a one way or two way... I thought two way but I think I've confused myself. Id be grateful for any help.

Hi Francesca,

I'd suggest a two way ANOVA with repeated measures on one factor:

Factor 1: sex (between subjects factor; two levels: male, female)

Factor 2: IQ estimates (within subjects factor; three levels: own, mother, father).

Sincerely,

Klaus Blischke

Thank you very much Klaus!

The differences between one- way and two-way ANOVA can be drawn clearly on the following grounds:

A hypothesis test that enables us to test the equality of three or more means simultaneously using variance is called One way ANOVA. A statistical technique in which the interrelationship between factors, influencing variable can be studied for effective decision making, is called Two-way ANOVA.

There is only one factor or independent variable in one way ANOVA whereas in the case of two-way ANOVA there are two independent variables.

One-way ANOVA compares three or more levels (conditions) of one factor. On the other hand, two-way ANOVA compares the effect of multiple levels of two factors.

In one-way ANOVA, the number of observations need not be same in each group whereas it should be same in the case of two-way ANOVA.

One-way ANOVA need to satisfy only two principles of design of experiments, i.e. replication and randomization. As opposed to Two-way ANOVA, which meets all three principles of design of experiments which are replication, randomization, and local control.

https://keydifferences.com/difference-between-one-way-and-two-way-anova.html

Thank you so much for your useful information.

Best regards.

Chafia.

Dear all,

Thanks for your time and elaborating the basic question that I also learnt a lot.@all

Dear all,

I'm doing research on how to improve age estimation in Pine tree (Pinus patula) one aspect that i have to examine is the age P. patula at 0cm, 20cm, 40cm and 60cm compare whether they differ or not. Please kindly advice me with statistical test to run.

Thank you in advance.

Read this one to understand the basics and how to perform ANOVA: https://reneshbedre.github.io/blog/anova.html

Hi everyone!

I am trying to understand whether there is a significant difference in taxonomic and functional diversity of microbial communities among different sides of a plant hummock.

Here is my research question: Is the taxonomic and functional diversity of soil microbial community heterogeneous within the same plant hummock?

So I have;

1. Dependent variable (Microbial community): 2 levels: taxonomic and functional diversity

2. Independent variable (Plant hummock): 4 levels; L1, L2, L3 & C1.

Would this be a Two-Way ANOVA?

Kindly follow this tutorial to clear your doubt: https://www.youtube.com/watch?v=Q116ZnLy5uA

What?

Following.....

What distinguishes a one-way ANOVA from a two-way ANOVA is the number of explanatory/ independent variables. In your question, the inclusion of "two dependent" variables suggests its plausibility as a determining factor, it is simply not.

In a one-way ANOVA, the key thing is you ONLY ONE explanatory/ independent variable. How many response/ independent variables available do not matter. For example, you are analysing effect of NPK fertiliser application rates on (1) Yield, (2) Growth, (3) Nutrient content, (4) etc, the number of these response variables do not make it a two-way or multiple ANOVA, it is still a one-way ANOVA on the basis of having one explanatory variable. Also, the number of levels do not determine a 2-way or 1-way ANOVA. You can have 3 or more (less than 3 will be a T-test) levels but will still be one-way as long as there is one factor; NPK application rates in this case.

Therefore, for an ANOVA to be called two-way, its when there are two explanatory variables regardless of how many levels each has. For example, you are assessing the effect of fertiliser application rates and cultivar differences on growth and yield of a particular crop. Here, in addition to fertiliser rates, you have another factor; cultivars. In this case, you have a two-way ANOVA. When they are more than two, say you add different agro-ecological zones, you have a multiple ANOVA. How you approach different ANOVAs depend on the experimental designs, such that in CRD, ANOVA will be different from RCBD. In 3 factors, A split plot experimental design works better and has a different statistical model and hence a different ANOVA.

Its also important to know that a response variable does not have levels, it is incorrect to name them as such, they are simply response variables e.g. growth, yield, nutrient content etc. Levels are used for explanatory variables.