Statistics: Correlation and Regression Analysis in SPSS

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  • Опубликовано: 21 авг 2024
  • This video shows how to use SPSS to conduct a Correlation and Regression Analysis. A simple null hypothesis is tested as well. The regression equation is explained despite the result of the hypothesis conclusion.
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Комментарии • 148

  • @DrMiaak
    @DrMiaak 11 лет назад

    Hi
    frankly speaking and allow me to say that your video is the most valuable, clear and simple video on YouToub.
    > simple and clear language
    > focus on the important areas (why, when, how..)
    > slow enough to understand and absorb
    > good example
    KEEP IT ON YOU ARE GOOD AT IT MAN (THUMB UP)

  • @Memoir_of_My_Own
    @Memoir_of_My_Own 10 лет назад +1

    We have learned for a whole semester about doing applied linguistics research and reading papers, yet our so-called professors never clearly impart us with the necessary SPSS techniques and reasonable analysis. They might themselves get baffled in understanding the data. It shames me to say that I am already an English postgraduate from an "eminent" university in China. So I am about to learn SPSS by myself. Thank you!

  • @jamillerichardson5679
    @jamillerichardson5679 7 лет назад +1

    This is by far the most enlightening and helpful tutorial I have viewed on the topic. I will seek more of your tutorials. Thank you so much!

  • @iheartseventeen
    @iheartseventeen 10 лет назад +1

    This is the best regression tutorial I've EVER watched. Everything was very clear and well explained. THANK YOU!!!!!!

  • @shubhamlahan
    @shubhamlahan 7 лет назад +20

    Man, This is the most clarifying tutorial I've come across. Thank you. Thanks a lot. You're doing a fantastic work. Keep it up. Best wishes to you. :)

  • @saintgregoiredarmeniemonas1817
    @saintgregoiredarmeniemonas1817 8 лет назад +1

    Excellent video, with CLEAR explanations, especially for SPSS novices and statistics allergics! Thank you for sharing!

  • @aminathmanal5621
    @aminathmanal5621 7 лет назад

    Finally I understood something. Its great that you have used the ppt parts to actually tell us what all those stand for teaching the basics. My dissertation draft is due tomorrow and this helped me a lot. Thank you so much.

  • @TheNaqja
    @TheNaqja 10 лет назад +1

    Thank you for this videos Prof. Agron.
    I am preparing my business statistics exam and your videos are very helpful.
    Si shqipetar nuk ju fshehi dot edhe emocionin qe me krijoj kur pash emrin tuaj, faleminderit shume!

    • @AGRONKACI
      @AGRONKACI  10 лет назад

      You're very welcome Nardi! Hope your business statistics is going well...

  • @isahshehu6249
    @isahshehu6249 6 лет назад +1

    Correlation and regression analysis were explicitly clarified to a logical conclusion in this video. Thanks a lot

  • @piusambros300
    @piusambros300 8 лет назад +1

    It really gives the clear concepts on improving the skills of statistical inference

  • @RSV4JeffA
    @RSV4JeffA 10 лет назад +1

    The best video I've seen on correlation and regression. Thanks.

  • @tamammohamad922
    @tamammohamad922 4 года назад +1

    This is a clear tutorial. You have explained it well, especially when you spoke of both the results, and you further went onwards to speak about PREDICTION. Thanks,

    • @tamammohamad922
      @tamammohamad922 4 года назад +1

      I wish I had the data access so that I could practice at the same time. The font is small also .

    • @AGRONKACI
      @AGRONKACI  Год назад

      I will make another video for correlation and regression, hopefully more qualitative than this one.

  • @yogambal.n6840
    @yogambal.n6840 5 лет назад +1

    What a crystal clear explanation sir, we are grateful to view this session .Let your service continues and light lamp for many who are in need

    • @AGRONKACI
      @AGRONKACI  5 лет назад

      Thank you. Appreciate it

  • @MRradicalmj
    @MRradicalmj 10 лет назад +2

    This was a very helpful video. Thank you for posting it

  • @13digitalmarketingsoftware39
    @13digitalmarketingsoftware39 9 лет назад

    Great video and great explanation.It makes Regression Analysis sound easy.Thank you!

  • @user-ho3xy6xr2n
    @user-ho3xy6xr2n Год назад

    Huge thumbs up... you deserve more than 5 stars for this great tutorial. Very helpful... many thanks! Jimmy Aldido

  • @Mwandeo
    @Mwandeo 3 года назад +1

    A very comprehensive presentation on correlation and regression. Keep it up Agron.

  • @sarimahmad883
    @sarimahmad883 2 года назад +3

    CRISP AND CLEAR!!!

  • @AGRONKACI
    @AGRONKACI  11 лет назад +1

    If p is smaller or equal to 0.05 you must reject the null hypothesis, if your alpha level (reference probability) is 5%. So, yes, reject it even if p=.05.

  • @dream_patisserie9
    @dream_patisserie9 7 лет назад +1

    Thank you so much!!! Your video help me a lots when i am suffering. Million thanks have to express for you. Appreciated

  • @Gertiksxx
    @Gertiksxx 11 лет назад

    Thanks Mr. Kaci !! This was very useful to me :)
    Best wishes from Albania!

  • @AliciaPrasana
    @AliciaPrasana 8 лет назад +1

    wonderful video. explains everything anyone needs needs to know for correlation and regression. thank you very much.

  • @ekalisty
    @ekalisty 11 лет назад

    Thanks for the very CLEAR explanation! It does help!!

  • @mayani71
    @mayani71 9 лет назад +3

    Great! Video and explanation.....Thank you so much for such a clear and concise tutorial.

  • @AGRONKACI
    @AGRONKACI  11 лет назад

    The p-value represents the chances that your Null Hyp is true. The smaller the p-value the less likely it is that your null will be true; therefore you reject it if the chances are less than 1 in 20, or 5 in 100 (hence 5%, or alpha 0.05) that it is true. P-value larger than 5% (this reference probability is chosen in advance - depending on the field or research, or on the seriousness of your work and test) show a greater likelihood that the null would be true, that's why you do not reject it.

  • @shpendnuredini9385
    @shpendnuredini9385 3 года назад +1

    Well done Mr. Agron! I'm proud of albanians like you.

  • @sherehanwahid3039
    @sherehanwahid3039 3 года назад +1

    Perfectly explained! Thank you so much, you made it very easy to comprehend.

  • @sumitapradhan2062
    @sumitapradhan2062 7 лет назад +1

    your explanation is clear and precise...thanks a lot

  • @zeekbt
    @zeekbt 8 лет назад +1

    It was very helpful Sir. Your effort is appreciated ! Thank You

  • @bimalajadhari2650
    @bimalajadhari2650 6 лет назад +1

    Thank you so much for this tutorial. You made is so easy to understand.

  • @mattthewstinkhathom-kafumb1839
    @mattthewstinkhathom-kafumb1839 5 лет назад +1

    Simply the best. Respect to you Sir.

  • @ikramnoor6332
    @ikramnoor6332 7 лет назад

    you have just made my concepts clear.. awesome tutorial...

  • @GanasoundariJoshua
    @GanasoundariJoshua 11 лет назад

    Your video is very simple and answered some of the basic questions I had. With regard to the value of constant, I was told that it refers to other factors that are affecting the independent variable other than what we have considered (in this video, GPA). Please let me know if I am right or pl explain

  • @anesdj4282
    @anesdj4282 9 лет назад +1

    Thank you for sharing these information and simplify it, I am dealing with multiple regression to assess the impact of the provenance of students (Home/International) and the course studied (MBA/MSc) on the employability of graduates in a University in the UK, as there are many independent variables, I am confused whether the correlation coefficient represents the correlation between all the variables (dependent and independent)!?

  • @neerjanglama4715
    @neerjanglama4715 4 года назад

    Thank you for the very simplified and clear explanation

  • @ninoalfonso79
    @ninoalfonso79 8 лет назад +2

    Thank you very much Sir, your explanation is very clear!

  • @aleksismil
    @aleksismil 8 лет назад +1

    Thank you for uploading this. It made things very clear!

  • @hossamhossam1706
    @hossamhossam1706 8 лет назад +2

    Thank you Mr. Argon but usually we look to the Beta and not B which is 0.271 (slope)...please clarify

  • @ankitmangla9780
    @ankitmangla9780 5 лет назад +1

    Thank you. Really helpful in understanding. Can you include more videos on how to write these results out in a manuscript? Thank you

  • @AGRONKACI
    @AGRONKACI  11 лет назад

    Your comment is very much appreciated! I'm glad you have liked it.

  • @bornhere13
    @bornhere13 10 лет назад +1

    I wish everything was explained like this!

  • @ielyzab2168
    @ielyzab2168 8 лет назад +1

    Thank you! Now I know what to do with my weak correlation!!!

  • @utubemania9079
    @utubemania9079 4 года назад

    That about 14 minutes vs my entire education.Bow to you.

  • @hit4success
    @hit4success 9 лет назад +1

    I tried several times to understand the correlation and regression but failed. This video helps me to understand

  • @khymfrance7354
    @khymfrance7354 11 лет назад

    Hi Sir,
    May i firstly thank you for such a clear and concise lecture on correlation and regression and secondly for some advice. I am currently comparing 4 indep variables to 1 depen to test correlation and which has highest sig. However all four have resulted in .000 sig. How do i determine which is now more statistically significant between the four? Your guidance would be much appreciated.

  • @ahmednourrein5495
    @ahmednourrein5495 4 года назад

    This is an interesting session. very simple and adding value for beginners. Awesome.

  • @ademtamo5677
    @ademtamo5677 6 лет назад +1

    Crystal clear. Thank you!

  • @Makinen689
    @Makinen689 11 лет назад

    thank you. very useful for my thesis.

  • @Nashty91
    @Nashty91 10 лет назад +1

    Awesome video. I am currently writing a research paper using these measures. How would I differentiate between correlation and regression? Just that correlation is based on observing if there is a relationship and regression deals with being able to predict the dependent based on the independent?

    • @AGRONKACI
      @AGRONKACI  9 лет назад +3

      That is basically it! However, mathematically, these concept are just about the same thing. Statistically, although you may see a high correlation between two variables, it does not necessarily mean that there is causation. Correlation, basically, tells you whether there is an association (existence), if this association is positive or negative (direction) and the strength of this association.

  • @webbert11
    @webbert11 10 лет назад +2

    If you've accepted your null hypothesis, then why would you then use your line formula as a predictor for age and GPA? I thought we just determined that age doesn't explain GPA with statistical significance?

    • @AGRONKACI
      @AGRONKACI  10 лет назад +4

      Hello Nicholas! Firstly, thank you for sharing my video! Much appreciated! Secondly, we never accept the null hypothesis, since we cannot create a new fake notion about the initial idea; we just fail to reject it, in which case we do not have enough evidence to accept the alternative hypothesis, which was our main research idea. Thirdly, the reason I explained the regression equation is for academic purposes only; just to show my students (in the video) how to properly set up and solve such an equation, the conclusion of the hypothesis notwithstanding. Thanks!

    • @annamelissa607
      @annamelissa607 9 лет назад

      Agron Kaci i have 4 question in questionnaire that represent dependent variable and 3 question in the questionnaire represent independent variable 1,how can i combine all this question to represent depended variable and independent variable 1 because i want to use dependent variable with Independence variable in correlation analysis?

    • @AGRONKACI
      @AGRONKACI  9 лет назад +1

      anna melissa
      Anna, yes, you can combine variables into one variable and then use the combined variable for statistical variables. However, my video does not demonstrate SPSS' commands. A simple search for how to combine variables will get you to where you want to be.

    • @annamelissa607
      @annamelissa607 9 лет назад

      why when i try doing my reliability test,i get cronbach alpha number section but i don't get any number from cronbach alpha if item deleted section? it just show a small letter (a) saying it was negative value?and say my coding is wrong?i check triple time already and nothing is wrong with my coding and key in data? :( the weird thing is i able to do the rest of analysis with that data :(

  • @raylk8842
    @raylk8842 11 лет назад

    Excellent explanation thank you so much!

  • @patrickqueen6558
    @patrickqueen6558 3 года назад +1

    very clear and straightforward thank you!

  • @jovan6347
    @jovan6347 6 лет назад +1

    Good and simple explanation.

  • @katherinemeuti8806
    @katherinemeuti8806 8 лет назад +1

    Thank you! This helps a lot! Do you have a video on confidence intervals?

  • @harsimrankaur7050
    @harsimrankaur7050 3 года назад

    amazing tutorial which i have seen so far

  • @AGRONKACI
    @AGRONKACI  11 лет назад

    You're welcome!

  • @breastcancersurgerybysanji7832
    @breastcancersurgerybysanji7832 7 лет назад

    Its really good. Thanks a lot. Waiting for more videos from you.

  • @KhalidFarooq786
    @KhalidFarooq786 4 года назад +1

    excellent presentation. well done

  • @mohammedfaizan1535
    @mohammedfaizan1535 5 лет назад +2

    Saw and really liked this video. But I have a confusion regarding my analysis, as my topic is 'Impact of brand extensions on parent brand image'. How can I find correlation and regression analysis when you have more than 2 variables. Would appreciate your response towards this.

    • @AGRONKACI
      @AGRONKACI  5 лет назад +1

      You need to do a multiple regression, where the independent variable field would have all your predictors, which seem to be "brand extensions".

  • @manarahmedkeshk8066
    @manarahmedkeshk8066 7 лет назад

    thank you for the amazing tutorial :) it is really simple and easy to digest :) you are amazing statistics teacher really thank you !

  • @kin8801
    @kin8801 11 лет назад

    Great lecture

  • @fikirtemariam
    @fikirtemariam 9 лет назад +1

    it is very helpful! Thank you so much!!

  • @victorvelayos1415
    @victorvelayos1415 10 лет назад

    I believe you should use a p-value of 1/100= 1%. Your confidence will be higher that you have the correct result ;)

  • @marufmamurovich3793
    @marufmamurovich3793 6 лет назад

    Amazing explanation!
    Thank you very much.

  • @littleJiao
    @littleJiao 9 лет назад +1

    Thank you so much! Very helpful!

  • @alensingson
    @alensingson 11 лет назад

    Thank you very much, it was very helpful

  • @barakhan8004
    @barakhan8004 9 лет назад +1

    Very helpful, thanks

  • @TheReedit
    @TheReedit 10 лет назад +1

    Thank you so much !

  • @hannahjung3431
    @hannahjung3431 7 лет назад

    It is so clear. Thank you so much.

  • @Slummob
    @Slummob 10 лет назад +2

    Excellent.

  • @manalahmadsamamahmas2213
    @manalahmadsamamahmas2213 6 лет назад +1

    Thank you very much ..do you have a video on multiple regression

  • @nangbaabright3224
    @nangbaabright3224 7 лет назад +1

    i love this tutorial

  • @transformeris7
    @transformeris7 11 лет назад

    great video! :) Helped a lot :)

  • @johanpieterdeborst4148
    @johanpieterdeborst4148 10 лет назад +1

    In your example you show firstly there is no correlation between the two variables, but, then, using the same variables, your regression equation shows a relationship between the two, hence the ability to predict. Is that possible with the same data? Or am I missing the point (that's fairly likely!)?

    • @Nashty91
      @Nashty91 10 лет назад +1

      That's what I am trying to figure out...

    • @murtazamansoor1626
      @murtazamansoor1626 10 лет назад +3

      Please note that there is a correlation between the two variables. It is just that such correlation is 'weak' (i.e. 0.271) which is less than 0.3. The regression analysis further supports this notion as it indicates that the strength of relationship given by the two variables used is only 7% meaning that there are other factors (amounting to 93%) that determine the relationship between the two variables.

    • @johanpieterdeborst4148
      @johanpieterdeborst4148 10 лет назад

      Murtaza Mansoor Excellent, thank you.

    • @AGRONKACI
      @AGRONKACI  9 лет назад +1

      Johan! Apologies for replying so late. Your question is excellent. The correlation coefficient, r= 0.271, is very small, therefore showing a weak correlation between the variables. The regression definitely shows the same thing, since mathematically, they crunch the same numbers the same way. Therefore, it logically follows that the relationship is insignificant. When the relationship is insignificant at the alpha level, we must retain the null hypothesis, therefore we find that we do not have enough evidence to accept the hypothesis that the relationship is significantly strong. Now, why did I bother and explained the regression equation when the model is insignificant? For pedagogical purposes! I did not want to create another video with other variables or datasets where I could find a significant association for regression purposes. That's all...

    • @johanpieterdeborst4148
      @johanpieterdeborst4148 9 лет назад

      Agron Kaci Thanks Agron!

  • @AGRONKACI
    @AGRONKACI  11 лет назад

    Thank you!

  • @MissSanaBA
    @MissSanaBA 8 лет назад

    Are correlation and regression analysis applicable as nonparametric tests? does it go with convenience type of sampling?

  • @darsaijaz1
    @darsaijaz1 10 лет назад

    Agron Kaci thanks for the tutorial, however I have a question , if I have to find the relationship between age and salary and the given salary is current annual salary and starting annual salary which test to use for it and which salary to choose as variable with age.

  • @NishanthaPriyananda
    @NishanthaPriyananda 11 лет назад

    Dear sir,
    Can you explain how we can analyze liker t scale questionnaire and
    use the result seeking mean,median,and standard divination including relation ships.thanks a lot sir

  • @HassanMohamed-vs4re
    @HassanMohamed-vs4re 7 лет назад

    I need more lecture to understand spss internationally

  • @arieyelle7751
    @arieyelle7751 6 лет назад +1

    Thank you sooo much Sir !!!!!

  • @prashantubarhande3523
    @prashantubarhande3523 10 лет назад +1

    best for learners........

    • @AGRONKACI
      @AGRONKACI  10 лет назад

      Thank you! Appreciated!

  • @DrMiaak
    @DrMiaak 11 лет назад

    My friend would you please tell me when we use correlation and when using Regression? as far as I know correlation is to examine the relation between IVs & DV but then what the regression is for? please simplify the answer as am not from statistic background.

  • @Syafika896
    @Syafika896 11 лет назад

    Thanks for showing the easiest way to understand about variables correlations. However my independent variable show -.143. So does the variable is not correlate with my dependent variable? does it show negative relation between two variables? after that i did multiple linear regression and again the number shown for my variable 1 is positive and my 2nd variable is negative. What does it mean? thanks for the help.

  • @doreenshamalaantoniomerino6358
    @doreenshamalaantoniomerino6358 7 лет назад

    Thank you very much.

  • @taklealamu3376
    @taklealamu3376 4 года назад +1

    Thank you very much

  • @eriseldamino8248
    @eriseldamino8248 7 лет назад +1

    Faleminderit 🇦🇱

  • @newmanomigie3046
    @newmanomigie3046 6 лет назад +1

    Thank you

  • @user-ng1fn8ff6b
    @user-ng1fn8ff6b 10 лет назад

    Thank you, I Need it.

  • @kuganeshvarieshvari3445
    @kuganeshvarieshvari3445 6 лет назад +1

    thanks you ..i need it

  • @ebenyiemekaonwe2971
    @ebenyiemekaonwe2971 5 лет назад +1

    Thank you so much

  • @kenneth1045
    @kenneth1045 6 лет назад +1

    thank you so much!!!

  • @SweetDarkey84
    @SweetDarkey84 11 лет назад

    Great...Stats made easy :-)

  • @mamtachaube
    @mamtachaube 9 лет назад +1

    thanks .it was helpful

  • @anissayuniashaesa881
    @anissayuniashaesa881 7 лет назад

    Hi, I have the same analysis. However, my age dataset is in range (ex: 0-7, 7-9, etc.). What should I do to analyse this? And should I choose R pearson correlation analysis? Thanks!

    • @AGRONKACI
      @AGRONKACI  7 лет назад

      Anissa Yuniashaesa
      Variable Age as you have it, makes an ordinal variable. Please make sure that you meet all the assumptions, one of which is the variable should be at least on an interval level of measurement.

  • @bdyasini1
    @bdyasini1 11 лет назад

    if p value is exactly 0.05, should we reject or accept the null hypothesis? thanx in a dvance

  • @namechosen1
    @namechosen1 11 лет назад

    thanks

  • @nyakoelamech
    @nyakoelamech 7 лет назад

    Say we have a project in finance that is tacking the effect of
    omni-channels business strategies on competitiveness of commercial
    banks. The channels are e-transaction, e-communication, e-banking, and
    e-finance, and these make up the independent variables of the study. In
    development of the questionnaire, each variable has 6 items/statements
    on a 5-point likert scale. Moreover, the dependent variable on
    competitiveness has six statements that should be rated on a likert
    scale. Now my question is, how do i carry out correlation analysis or
    regression analysis going by the fact that there exist so many
    statements under one variable?

    • @AGRONKACI
      @AGRONKACI  7 лет назад +1

      I would think that you may need analysis of association, hence chi-square (cross tabulation), because your data is ordinal, not ratio.

    • @nyakoelamech
      @nyakoelamech 7 лет назад

      That is well understood. How do you go about variables of the study (independent) in a questionnaire having particular statements, say five each and requiring responses on a 5-point likert scale, and you need to carry out regression analysis? In SPSS, all these statements/items of individual variables will be there once you click on regression then linear. Help here.

  • @passanggaljensherpa4454
    @passanggaljensherpa4454 6 лет назад

    nice explanation

  • @kavanpuranik98
    @kavanpuranik98 2 года назад

    Is the value of alpha 0.05 by default? For all calculations and any set of data while using linear regression?

    • @AGRONKACI
      @AGRONKACI  Год назад +1

      Kavan Puranik,
      In social sciences, probability level is usually 5%. This value is to guard against making Type I Error, where you fear that you will reject a true null hypothesis. A true Ho would be when data shows no relationship or difference. For example, when you want all your products to be the same and they are, but you by mistake reject that and decide that some of your products are different. Because you think they are different (when they are not) then they are not fit for sale, and you have to throw all of them in trash and make others. This error cost your business. However, 5% error is generally tolerable.
      If you want to guard more sensitive things in like, such as health, then you may want to use 1% probability level, or 0.01 significance level. This can be when testing new medicine, for example. You should not tolerate a lot of error in medicine, because that may affect health and life.
      Hope this helped.