Ubahpecahan menjadi desimal di Excel. Ikuti langkah-langkah di bawah ini untuk mengubah bilangan pecahan menjadi bilangan desimal normal di Excel. 1. Pilih bilangan pecahan yang akan Anda ubah, klik kanan dan pilih Format Cells dari menu konteks. Lihat tangkapan layar: 2. di Format Cells kotak dialog, klik untuk menyorot Umum dalam Kategori
Converting an SPSS string variable into a numeric one is simple. However, there's a huge pitfall that few people are aware of string values that can't be converted into numbers result in system missing values without SPSS throwing any error or warning. This can mess up your data without you being aware of it. Don't believe me? I'll demonstrate the problem -and the solution- on part of which is shown below. SPSS Strings to Numeric - Wrong Way First off, you can convert a string into a numeric variable in variable view as shown below. Now, I never use this method myself because I can't apply it to many variables at once, so it may take way more effort than necessary; it doesn't generate any syntax there's no Paste button and nothing's appended to my journal file; it can mess up the data. However, there's remedies for that. So What's the Problem? Well, let's do it rather than read about it. We'll set empty cells as user missing values for s3; convert s3 to numeric in variable view; run descriptives on the result. *Set empty string as user missing value for values s3 ''.*Inspect frequency table for s3.*Now manually convert s3 to numeric under variable view.*Inspect s3.*N = 444 instead of 459. That is, 15 values failed to convert and we've no clue why. Result Note that some values in our string variable have been flagged with “a”. We probably want these to be converted into numbers. We have 459 valid values non empty cells. After converting our variable to numeric, we ran some descriptives. Note that we only have N = 444. Apparently, 15 values failed to convert -probably not what we want. And we usually won't notice this problem because we don't get any warning or error. Conversion Failures - Simplest Solution Right, so how can we perform the conversion safely? Well, we just inspected frequency tables how many non empty values do we have before the conversion? converted our variables to numeric; inspected N in a descriptive statistics after the conversion. If N is lower than the number of non empty string values frequencies before conversion, then something may be wrong. In our first example, the frequency table already suggested we must remove the “a” from all values before converting the variable. We'll do just that in a minute. Although safe, I still think this method is too much work, especially for multiple variables. Let's speed things up by using some handy syntax. SPSS - String to Numeric with Syntax The fastest way to convert string variables into numeric ones is with the ALTER TYPE command. It allows us to convert many variables with a single line of syntax. The syntax below converts all string variables in one go. We then check a descriptives table. If we don't have any system missing values, we're done. SPSS ALTER TYPE Example *Close data without saving and reopen before proceeding.*Convert all variables in one type s1 to s3 f1 s4 s1 to s4. Note using alter type s1 to s4 f1. will also work but the decimal places for s4 won't be visible. This is why we set the correct f format means 6 characters including the decimal separator and 3 decimal places as in Which is the format of our string values. Result Since we've 480 cases in our data, we're done for s1. However, the other 3 variables contain system missings so we need to find out why. Since we can't undo the operation, let's close our data without saving and reopen it. Solution 2 Copy String Variables Before Conversion Things now become a bit more technical. However, readers who struggle their way through will learn a very efficient solution that works for many other situations too. We'll basically copy all string variables; convert all string variables; compare the original to the converted variables. Precisely, we'll flag non empty string values that are system missing after the conversion. As these are at least suspicious, we'll call those conversion failures. This may sound daunting but it's perfectly doable if we use the right combination of commands. Those are mainly STRING, RECODE, DO REPEAT and IF. Copy and Convert Several String Variables *Close data without saving and reopen before proceeding.*Copy all string c1 to c4 a7.recode s1 to s4 else = copy into c1 to c4.*Convert variables to type s1 to s3 f1 s4 each variable, flag conversion failures cases where converted value is system missing but original value is not repeat conv = s1 to s4 / ori = c1 to c4 / flags = flag1 to and ori '' flags = repeat.*If N > 0, conversion failures occurred for some flag1 to flag4. Result Only flag3 and flag4 contain some conversion failures. We can visually inspect what's the problem by moving these cases to the top of our dataset. *Visually inspect why values fail to cases by flag3 d.*Some values flagged with 'a'.sort cases by flag4 d.*Some values flagged with 'a' through 'e'. Result Remove Illegal Characters, Copy and Convert Some values are flagged with letters “a” through “e”, which is why they fail to convert. We'll now fix the problem. First, we close our data without saving and reopen it. We then rerun our previous syntax but remove these letters before the conversion. Syntax *Close data without saving and reopen before proceeding.*Copy all c1 to c4 a7.recode s1 to s4 else = copy into c1 to c4.*Remove 'a' from s3 = replaces3,'a',''.*Remove 'a' through 'e' from repeat char = 'a' 'b' 'c' 'd' 'e'.compute s4 = replaces4,char,''.end repeat.*Try and convert variable type s1 to s3 f1 s4 conversion failures repeat conv = s1 to s4 / ori = c1 to c4 / flags = flag1 to and ori '' flags = repeat.*Inspect if conversion flag1 to flag4.*N = 0 for all flag variables so we're done.*Delete copied and flag variables c1 to flag4. Result All flag variables contain only system missings. This means that we no longer have any conversion failures; all variables have been correctly converted. We can now delete all copy and flag variables, save our data and move on. Thanks for reading!
Copypaste data desimal dari excel ke spss, kok jadi DATA ribuan ? - YouTube.
Jika Anda sering menggunakan program statistik SPSS untuk analisis data, Anda mungkin pernah mengalami kesulitan saat menampilkan atau mengubah angka desimal. SPSS sering kali secara otomatis menampilkan angka dalam format desimal tertentu, yang mungkin tidak sesuai dengan kebutuhan Anda. Namun, jangan khawatir karena cara mengubah desimal di SPSS cukup mudah dan sederhana. Langkah 1 Buka Dataset di SPSS Langkah pertama yang harus Anda lakukan adalah membuka dataset yang akan diubah desimalnya. Anda bisa membuka dataset yang sudah ada atau membuat dataset baru. Jika Anda sudah membuka dataset, maka langkah berikutnya adalah memilih variabel yang ingin diubah format desimalnya. Langkah 2 Pilih Variable View Pada tab bawah jendela SPSS, Anda akan melihat dua tampilan Data View dan Variable View. Pilihlah Variable View dengan mengklik tombol yang sesuai. Langkah 3 Pilih Variabel yang Ingin Diubah Setelah memilih Variable View, Anda akan melihat daftar variabel yang ada di dataset Anda. Pilihlah variabel yang ingin Anda ubah desimalnya dengan mengklik nama variabel tersebut. Langkah 4 Ubah Format Desimal Setelah memilih variabel yang ingin diubah, pada kolom “Type” pilih “Numeric”. Kemudian, pada kolom “Decimal Places”, ketikkan jumlah desimal yang diinginkan. Misalnya, jika Anda ingin menampilkan dua angka desimal, ketikkan angka 2 pada kolom tersebut. Langkah 5 Simpan dan Tampilkan Hasil Setelah menyelesaikan langkah-langkah di atas, klik “OK” untuk menyimpan perubahan. Selanjutnya, kembali ke Data View dan tampilkan hasilnya. Sekarang, angka pada variabel yang Anda ubah desimalnya sudah sesuai dengan yang Anda inginkan. Catatan Penting Ada beberapa hal yang perlu diperhatikan saat mengubah desimal di SPSS Perubahan pada variabel hanya berlaku untuk dataset yang sedang dibuka. Jika Anda ingin mengubah variabel di dataset lain, Anda harus membuka dataset tersebut terlebih dahulu. Perubahan pada variabel bersifat permanen. Jika Anda ingin mengembalikan format desimal ke semula, Anda harus mengulang langkah-langkah di atas. Beberapa format desimal dapat menyebabkan perbedaan hasil yang signifikan dalam analisis statistik. Oleh karena itu, pastikan Anda memilih format desimal yang sesuai dengan tujuan analisis Anda. Kesimpulan Mengubah desimal di SPSS sangat penting untuk memudahkan analisis data. Dengan mengikuti langkah-langkah di atas, Anda dapat mengubah format desimal pada variabel dengan mudah dan cepat. Namun, pastikan Anda memahami betul konsekuensi dari perubahan format desimal dalam analisis data Anda. Selamat mencoba!
Masukkaninput data kedalam SPSS, seperti berikut: Klik Analyze, terus pilih Descriptive statistics dan pilih Explore. Seperti gambar di bawah ini. Sebenarnya pilih descriptive juga bisa. Tapi hasilnya akan sama dengan explore. Dan pada explore itu hasilnya lebih banyak. Setelah diklik maka akan muncul jendela sebagai berikut.
TutorialSPSS Bahasa Indonesia, Pengenalan SPSS, Belajar SPSS,Menghitung data Statistik dengan SPSS, SPSS untuk Pemula,SPSS untuk Penelitian,
Pendahuluandan Pengenalan SPSS A. Pendahuluan. Aplikasi ilmu statistika dapat dibagi dalam dua bagian: 1. Statistik Induktif membuat berbagai inferensi terhadap sekumpulan data yang berasal dari suatu sampel. Tindakan inferensi tersebut seperti melakukan perkiraan besaran populasi, uji hipotesis, peramalan, dan sebagainya.
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cara mengubah desimal di spss
